Distributed storage and computing of interim data

ABSTRACT

A method begins by a set of distributed storage and task (DST) execution units receiving a set of partial tasks and data, where a partial task of the set of partial tasks includes a common task and a unique partial sub-task. The method continues with the set of DST execution units executing the common task on the data to produce a set of preliminary partial results. The method continues with a first DST execution unit of the set of DST execution units generating first interim data based on the at least some of the set of preliminary partial results. The method continues with the first DST execution unit executing a first unique partial sub-task on at least one of a first portion of the data and the first interim data to produce a first partial result.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority under 35U.S.C. §119(e) to the following U.S. Provisional Patent pplication,which is hereby incorporated herein by reference in its entirety andmade part of the present U.S. Utility patent application for allpurposes:

-   1. U.S. Provisional Application Ser. No. 61/679,007, entitled “TASK    PROCESSING IN A DISTRIBUTED STORAGE AND TASK NETWORK,” (Attorney    Docket No. CS01142), filed Aug. 2, 2012, pending.

The present U.S. Utility patent application further claims priorityunder 35 U.S.C. §120 as a continuation-in-part (CIP), to the followingU.S. Utility patent application, which is hereby incorporated herein byreference in its entirety and made part of the present U.S. Utilitypatent application for all purposes:

-   2. U.S. Utility application Ser. No. 13/707,428, entitled    “DISTRIBUTED COMPUTING IN A DISTRIBUTED STORAGE AND TASK NETWORK,”    (Attorney Docket No. CS00995), filed Dec. 6, 2012, pending, which    claims priority pursuant to 35 U.S.C. §119(e) to the following U.S.    Provisional Patent Application:    -   a. U.S. Provisional Application Ser. No. 61/569,387, entitled        “DISTRIBUTED STORAGE AND TASK PROCESSING,” (Attorney Docket No.        CS01000), filed Dec. 12, 2011.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

NOT APPLICABLE

BACKGROUND OF THE INVENTION TECHNICAL FIELD OF THE INVENTION

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

DESCRIPTION OF RELATED ART

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work station, video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersedstorage error encoding module in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage error decoding module in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of storing data inaccordance with the present invention;

FIG. 41 is a flowchart illustrating another example of storing data inaccordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 42B is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 42C is a flowchart illustrating an example of encrypting slices inaccordance with the present invention;

FIG. 42D is a schematic block diagram illustrating another embodiment ofa distributed storage and task (DST) execution unit in accordance withthe present invention;

FIG. 42E is a flowchart illustrating an example of decrypting slices inaccordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 43B is a flowchart illustrating another example of encryptingslices in accordance with the present invention;

FIG. 43C is a schematic block diagram illustrating another embodiment ofa distributed storage and task (DST) execution unit in accordance withthe present invention;

FIG. 43D is a flowchart illustrating another example of decryptingslices in accordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage error encoding module in accordance with the presentinvention;

FIG. 44B is a schematic block diagram of an embodiment of an encryptionengine in accordance with the present invention;

FIG. 44C is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 44D is a flowchart illustrating an example of encoding slices inaccordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage (DS) error decoding module in accordance with thepresent invention;

FIG. 45B is a schematic block diagram of an embodiment of a decryptionengine system in accordance with the present invention;

FIG. 45C is a flowchart illustrating an example of decoding slices inaccordance with the present invention;

FIG. 46A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 46B is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 46C is a flowchart illustrating an example of storing an interimresult in accordance with the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 47B is a flowchart illustrating an example of authorizing a partialtask execution request in accordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;and

FIG. 48B is a flowchart illustrating an example of obtaining a datarecord in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsincludes, but is not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an 10 interface module 60, at least one 10 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terra-Bytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terra-Bytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terra-Bytes) into 100,000 data segments, each being 1 Giga-Byte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The group selecting module 114 outputs the slice groupings96 to the corresponding DST execution units 36 via the network 24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, wherein in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of datasegments 156 for a given data partition, the slicing module outputs aplurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—1)and ES1-2) of the first set of encoded data slices include errorcorrection data based on the first-third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—1)and ES1_(—2)) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—1)) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—2)) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—3)) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—4), whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—5), which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or andthe other analog and/or digital processing circuitry), availability ofthe processing resources, etc. If the controller 86 determines that theDT execution module(s) 90 have sufficient capabilities, it generatestask control information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results may 102 also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identity of other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step executing the task in accordance with the task controlinformation 176, the DT execution module 90 retrieves the encoded slicesfrom memory 88. The DT execution module 90 then reconstructs contiguousdata blocks of a data partition. As shown for this example,reconstructed contiguous data blocks of data partition 1 include datablocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbounded DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—1)).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of a de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupselection module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The group selecting module 114 groups the encoded slices 218 of the datasegments into pillars of slices 216. The number of pillars correspondsto the pillar width of the DS error encoding parameters. In thisexample, the distributed task control module 118 facilitates the storagerequest.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Salomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terra-Bytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distributions modules location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few terra-bytes or more),addressing information of Addr_(—)1_AA, and DS parameters of ⅗;SEG_(—1); and SLC_(—1). In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., ⅗ for the first data entry), segmentsecurity information (e.g., SEG_(—1)), per slice security information(e.g., SLC_(—1)), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of ⅗; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slice names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., ⅗ for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1_(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or and other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words or/or phrases intranslated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compareto ID errors (ordered after task 1-4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of ⅗ for their decode threshold/pillar width; hence spanningthe memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words).

Task 1_(—)3 (e.g., translate) includes task execution information asbeing non-ordered (i.e., is independent), having DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate data partitions2_(—)1 through 2_(—)4 and having DT execution modules 1_(—)2, 2_(—)2,3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5 through 2_zto produce task 1_(—)3 intermediate results (R1-3, which is thetranslated data). In this example, the data partitions are grouped,where different sets of DT execution modules perform a distributedsub-task (or task) on each data partition group, which allows forfurther parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3_z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3_z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specific translatedwords and/or phrases in the partitions of the translated data (R1-3_(—)1through R1-3_z) to produce task 3_(—)2 intermediate results (R3-2, whichis a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2_m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_(—)4 to produce partial results 102(e.g., 1st through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terra-Byte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of another embodiment of adistributed computing system that includes a plurality of distributedstorage and task (DST) processing units 16 and a distributed storage andtask network (DSTN) module 22. Each DST processing unit 16 of theplurality of DST processing units 16 includes an interface 30, a DSTclient module 34, and an interface 32. The DSTN module 22 includes a setof DST execution units 36. For example, the DSTN module 22 includes fiveDST execution units 36 when a pillar width is five.

The system functions to store data 350 as a plurality of sets of encodeddata slices 351 in the DSTN module 22. The data 350 may be retrievedfrom the DSTN module 22 when at least a decode threshold number ofencoded data slices per set of the plurality of sets of encoded dataslices 351 are available. A DST client module 34 receives the data 350via the interface 30 and encodes the data 350 to produce the pluralityof sets of encoded data slices 351 for storage in at least a decodethreshold number of DST execution units 36 of the set of DST executionunits 36. For example, the DST client module 34 sends two sets ofencoded data slices 351 to the DSTN module 22, where each set includestwo of each of pillar 1 slices, pillar 2 slices, pillar 3 slices, pillar4 slices, and pillar 5 slices.

Each DST client module 34 of the plurality of DST processing unit 16 maysimultaneously receive the data 350, encode the data 350 to produceslices 351, and send the slices 351 to the set of DST execution units 36for storage therein. Each DST execution unit 36 may be associated with aunique slice ingest rate 352 as compared to slice ingest rates 352 ofother DST execution units 36. Each DST client module 34 may determine awrite threshold when storing the data 350 in the DSTN module 22 based onslice ingest rates 352 of the set of DST execution units 36. The writethreshold is greater than or equal to the decode threshold and less thanor equal to the pillar width. For example, the DST client module 34determines the write threshold to be 4 based on a current slice ingestrate of the set of DST execution units 36 when the decode threshold is 3and the pillar width is 5. In such an example, the DST client module 34sends 4 slices per set of the plurality of sets of encoded data slicesto four of the DST execution units 36 for storage therein.

In an example of operation, the DST client module 34 of a first DSTprocessing unit 16 receives the data 350 via interface 30 and encodesthe data 350 to produce the plurality of sets of encoded data slices351. The DST client module 34 determines the write threshold based onone or more of a reliability level goal, a speed threshold goal, aningest rate of the data, a predetermination, a look up, a request, aquery, a test, and input/output load placed on the set of DST executionunits 36 by one or more other DST processing units 16, and an ingestrate 352 associated with each DST execution unit 36 of the set of DSTexecution units 36. For example, the DST client module 34 sends a firstset of encoded data slices 351 to the set of DST execution units 36 andmonitors ingestion performance to determine an ingest rate capabilityassociated with each DST execution unit 36. For instance, a first DSTexecution unit 36 ingests pillar 1 slices at a rate of 90 MB per second,a second DST execution unit 36 ingests pillar 2 slices at a rate of 100MB per second, a third DST execution unit 36 ingests pillar 3 slices ata rate of 85 MB per second, a fourth DST execution unit 36 ingestspillar 4 slices at a rate of 80 MB per second, and a fifth DST executionunit 36 ingests pillar 5 slices at a rate of 70 MB per second. Next, theDST client module 34 selects the write threshold to be three anddetermines to utilize the first, the second, and the third DST executionunit 36 to ingest the read threshold number of encoded data slices perset of encoded data slices 351 since those DST execution units 36 have afavorable ingestion rate capability level.

As another example, DST client module 34 obtains input/output loadinformation from other DST processing unit 16 of the plurality of DSTprocessing units 16 to determine available access capacity of each DSTexecution unit 36. The method of operation of the DST client module 34where this example is discussed in greater detail with reference to FIG.41. The DST client module 34 sends the write threshold number of encodeddata slices per set of encoded data slices three and 51 to acorresponding write threshold number of DST execution units 36 of theset of DST execution units 36. The DST client module 34 may facilitaterebuilding of other encoded data slices per set of encoded data slicesthree and 51, where the other encoded data slices were not written tocorresponding DST execution units 36.

FIG. 40B is a flowchart illustrating an example of storing data. Themethod begins at step 354 where a processing module (e.g., of adistributed storage and task (DST) client module) encodes data toproduce a plurality of sets of encoded data slices utilizing a dispersedstorage error coding function. The method continues at step 356 wherethe processing module generates one or more sets of write slice requeststhat includes a corresponding one or more sets of encoded data slices ofthe plurality of sets of encoded data slices. The generating may includedetermining the number of the one or more sets of write slice requestsbased on at least one of a predetermination, a historic number torealize reliable ingest speed data, and a request. For example, theprocessing module determines to send five sets of encoded data sliceswhen reliable ingest speed data has been historically obtained utilizingfour sets of encoded data slices.

The method continues at step 358 where the processing module outputs theone more sets of write slice requests to a set of DST execution units.For each DST execution unit of a set of DST execution units, the methodcontinues at step 360 where the processing module determines a dataingest rate of a set of data ingest rates. The determining may be basedon one or more of a query, a speed test, a lookup, and receiving anerror message.

The method continues at step 362 where the processing module determinesa write threshold number of DST execution units of the set of DSTexecution units based on the set of data ingest rates. The determiningmay be further based on one or more of an estimated reliability levelfor data storage, a reliability level threshold, an estimated accessspeed, a lowest access speed of the write threshold number of DSTexecution units, a speed threshold, an access capability estimator, apredetermination, an estimated rebuilding impact, a rebuilding impactthreshold, and a lookup. For example, a processing module determines toutilize a first, a third, a fourth and a fifth DST execution unit of theset of DST execution units to realize the write threshold of four for aset of five DST execution units, when the first, the third, the fourth,and the fifth DST execution unit each have an estimated access speedgreater than the speed threshold, and the estimated rebuilding impactcompares favorably to the rebuilding impact threshold for rebuildingslices of a second DST execution unit of the set of DST execution units.

The method continues at step 364 where the processing module determinesa transmit data rate such that the transmit data rate compares favorably(e.g., greater than or equal to) to a lowest data ingest rate of thewrite threshold number of DST execution units. For example, theprocessing module determines the transmit data rate to be 70 MB persecond when the lowest data ingest rate of the write threshold number ofDST execution units is 70 MB per second. For each remaining set ofencoded data slices of the plurality of sets of encoded data slices, themethod continues at step 366 where the processing module generates awrite threshold number of write slice requests, where each requestincludes a corresponding encoded data slice of a write threshold numberof encoded data slices. For example, the processing module generateswrite slice requests for pillars one, three, four, and five when DSTexecution units one, three, four, and five have been selected as part ofthe write threshold number of DST execution units.

The method continues at step 368 where the processing module outputs thewrite threshold number of write slice requests to the write thresholdnumber of DST execution units of the set of DST execution units inaccordance with the transmit data rate. For example, the processingmodule outputs slices to each of the write threshold number of DSTexecution units at a rate of 70 MB per second when the transmit datarate is 70 MB per second. The for each of the remaining sets of encodeddata slices of the plurality of sets of encoded data slices, the methodcontinues at step 370 where the processing module facilitates rebuildingother encoded data slices (e.g., slices not written). The facilitatingincludes at least one of directly rebuilding, rebuilding in accordancewith a schedule to achieve a loading goal, and sending a rebuildingrequest to a rebuilding module.

FIG. 41 is a flowchart illustrating another example of storing data. Themethod begins at step 372 where a processing module (e.g., of adistributed storage and task (DST) client module of a DST processingunit) determines to access a set of DST execution units with regards todata that is encoded to produce a plurality of sets of encoded dataslices. The accessing includes at least one of reading a slice andwriting a slice. The determining may be based on one or more ofreceiving a retrieval request, receiving a rebuilding request, andreceiving a storage request.

For each other DST processing unit of a plurality of DST processingunits that includes the DST processing unit, the method continues atstep 374 where the processing module determines a data loading level forthe set of DST execution units. The data loading level includes inputand/or output loading metrics for access to each DST execution unit ofthe set of DST execution units with regards to the DST processing unit.The determining may be based on one or more of a query, a test,monitoring loading levels, receiving a list, and receiving loadinginformation as part of an access request. For example, the processingmodule queries for DST processing units for a data loading level withregards to the set of DST execution units when the processing moduledetermines that five DST processing units are accessing the set of DSTexecution units, wherein the five DST processing units includes the DSTprocessing unit.

The method continues at step 376 where the processing module determinesan access rate based on the plurality of data loading levels. Theprocessing module determines the access rate such that the access rateplus an aggregate of the plurality of data loading levels is less thanan access capability level of the set of DST execution units. The methodcontinues at step 378 where the processing module determines an accessthreshold number of DST execution units of the set of DST executionunits based on the access rate. The determining includes identifying aloading level for each DST execution unit in determining the accessthreshold number by dividing the access rate by a lowest loading levelof a set of loading levels. The method continues at step 380 where theprocessing module generates a plurality of access threshold number ofslice access requests corresponding to the plurality of encoded dataslices. The method continues at step 382 where the processing moduleoutputs the plurality of access threshold number of slice accessrequests to the access threshold number of DST execution units inaccordance with the access rate.

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system that includes a DST client module 34coupled to a set of dispersed storage and task (DST) execution units 1-xvia a network 24 (not shown). The DST client module 34 includes anencoding module, a sub-set partitioning module, two chunk set groupingmodules, two outputting modules, a task partitioning module, a keygenerator 386, and a plurality of encryptor modules. The set of DST EXunits 1-x are divided into a primary set that includes DST EX units 1-kand a redundancy set that includes DST EX units m-x, where k, m, and xare integers and where x is greater than m and m is greater than k.

In an example of operation, the DST client module 34 receives data 92and a task 94 to be performed on the data 92. The task partitioningmodule partitions the task 94 into a set of partial tasks (e.g., partialtasks 1-k). The task partitioning module determines which DST EX unitsof the set of DST EX units 1-x that will perform the partial tasks onrespective encoded and encrypted portions of the data 92. For example,the task partitioning module determines that the DST EX units 1-k of theprimary set will perform the partial tasks.

With respect to the data, the DST client module 34 divides it into datasegments. The encoding module encodes a data segment in accordance witherror encoding parameters of a dispersed storage error encoding functionto produce a set of encoded data slices. For example, the error encodingparameters indicate a total number of encoded data slices are to becreated for each data segment, a decode number of encoded data slicesthat is needed to recover the data segment, and a redundancy number ofencoded data slices, which is the total number minus the decode number.The error encoding parameters may indicate further encoding informationsuch as the type of error encoding to perform, where the data segmentsare to be encrypted prior to encoding, whether integrity information isto be created for the data segment prior to encoding, whether integrityinformation is to be created for each encoded data slice, etc.

For each set of encoded data slices, the sub-set partitioning moduledivides a set of encoded data slices into a data slice set (e.g., thedecode threshold number of encoded data slices) and into a redundancydata slice set (e.g., the redundancy number of encoded data slices). Thesub-set partitioning module sends data slice sets to a first chunk setgrouping module and sends redundancy data slices sets to a second chunkset grouping module.

The first chunk set grouping module groups a plurality of data slicesets (e.g., two or more) into a chunkset of slices. The second chunk setgrouping module groups a plurality of redundancy data slice sets (e.g.,two or more) into a chunkset of redundancy slices. For example, assumethat the encoding module encodes a data segment into five encoded dataslices; three of which are needed to recover the data segment and twoare for redundancy. As such, the three encoded data slices are in theencoded data slice set and the two encoded data slices are in theredundancy data slice set. The first chunk set grouping module groupsthe three encoded data slices from a plurality of data segments into achunk set of slices and the second chunk set grouping module groups thetwo encoded data slices from the plurality of data segments into a chunkset of redundancy slices.

The first outputting module receives chunksets of slices from the firstchunk set grouping module and, for each chunkset of slices, divides andthen outputs them as sub-chunksets of slices (e.g., chunkset 1 slices,chunkset 2 slices, . . . chunkset k slices). Continuing with the exampleabove where each data segment requires three encoded data slices torecover the data segment, the first outputting module divides a chunksetof slices into three subsets, where an encoded data slice from each ofthe encoded data segments is included in each of the subset of chunksetof slices. As a more specific example, assume that a chunkset of slicesincludes encoded data slices for three data segments (e.g., EDS 1-1, EDS1-2, EDS 1-3, EDS 2-1, EDS 2-2, EDS 2-3, EDS 3-1, EDS 3-2, and EDS 3-3,where EDS means encoded data slices, the first number represents thedata segment, and the second number represents the slice number for thedata segment). For this specific example, the first outputting modulecreates a first sub-chunkset of EDS 1-1, EDS 2-1, and EDS 3-1; a secondsub-chunkset of EDS 1-2, EDS 2-2, and EDS 3-2; and a third sub-chunksetof EDS 1-3, EDS 2-3, and EDS 3-3.

The first outputting module sends the first sub-chunkset of slices to afirst encryptor module, the second sub-chunkset of slices to a secondencryptor, and so on. The first encryptor module encrypts the firstsub-chunkset of slices using a first unique key set to produce anencrypted sub-chunkset of slices (e.g., encrypted chunk set 1 slices).Similarly, each of the other encryptor modules (e.g., encryptor 2through encryptor k) encrypts its respective sub-chunkset of slicesusing a respective unique key set to produce a respective encodedsub-chunkset of slices.

The key generator module 386 generates each of the unique key sets forthe encryptor modules based on an assigned partial task, informationregarding a targeted DST EX unit (e.g., ID of the unit, a public key ofa public/private key pair of the unit, etc.), information regarding thekey generation (e.g., encryption algorithm, key seed, the data beingencrypted, etc.), and/or a pseudo random function. The key generatormodule 386 may generate a new unique key set for each new sub-chunksetof slices or the same unique key set may be used for multiplesub-chunkset of slices. In addition, the key generator module 386 maygenerate one or more keys for a given unique key set. For example, thekey generator module 386 may generate three keys for a given unique keyset when the corresponding sub-chunkset of slices includes three sets ofa decode number of encoded data slices. As a specific example, with thefirst sub-chunkset of slices includes EDS 1-1, EDS 2-1, and EDS 3-1, thekey generator module generates a first key for EDS 1-1, a second key forEDS 2-1, and a third key for EDS 3-1. As another specific example, thekey generator module generates one key for encrypting EDS 1-1, EDS 2-1,and EDS 3-1 of the first sub-chunkset of slices.

The encryptor modules output the encrypted sub-chunkset of slices to DSTEX units 1-k of the primary set. Each of the DST EX units 1-k decryptsits respective encrypted sub-chunkset of slices to recover thesub-chunkset of slices. Each of the DST EX units 1-k then performs itsassigned partial task on the recovered sub-chunkset of slices to producea partial result. Examples of this were previously discussed.

The second outputting module receives the chunkset of redundancy slicesand divides them into sub-chunksets of redundancy slices (e.g., chunkset1 of redundancy slices, . . . , chunkset n of redundancy slices). Thesecond outputting module then sends each sub-chunkset of redundancyslices to a respective one of the DST EX units in the redundancy set.

FIG. 42B is a schematic block diagram of another embodiment of acomputing device 390 and a set of distributed storage and task (DST)execution units 391. The DST execution units set 391 is divided into aprimary set 392 of DST EX units 36 and a redundancy set 394 of DSTexecution units 36. The computing device 390 may be implementedutilizing at least one of a DST processing unit, a DS processing unit, auser device, a DST execution unit, and a DS unit. The computing device390 includes a DST client module 34, which includes an encode module400, an encrypt module 402, and an output module 404.

The system functions to reliably and securely store data 406 in the DSTexecution unit set 391 to facilitate processing of one or moredistributed computing tasks on the data 406. The storing includes threeprimary functions: encoding the data 406; encrypting the encoded data,and sending the encrypted data to the DST execution unit set 391 forperformance of a task thereon. To encode the data 406, the encode module400 encodes the data 406 using a dispersed storage error encodingfunction to produce a plurality of sets of encoded data slices, where aset of encoded data slices includes encoded data slices and redundancyencoded data slices. For example, the encoded data slices includes adecode threshold number of encoded data slices and the redundancyencoded data slices includes a pillar width minus the decode thresholdnumber of encoded data slices.

The encoding module 400 arranges the encoded data slices d intochunksets of slices 410 and arranges the redundancy encoded data slicesinto chunksets of redundancy slices 412. For example, the encode module406 creates a chunkset of slices 410 to include encoded data sliceshaving a common pillar number.

The encode module 400 selects the primary set 392 (e.g., henceforthinterchangeably described as a set of primary storage and executionunits) from the set 391 to store the chunksets of slices 410 and selectsthe redundancy set 394 (e.g., henceforth interchangeably described as aset of redundancy storage and execution units) of the set 391 to storethe chunksets of redundancy slices 412. Having identified the primaryset 392, the encode module 400 assigns partial tasks 414 of the tasks408 to the set of primary storage and execution units 392 (e.g.,assigned based on processing requirements and capabilities).

The encrypt module 402 generates a unique key set for each DST EX unit396 based on the assigned partial task 414 (e.g., a task identifier, abit pattern of the task), information regarding the correspondingprimary storage and execution unit (e.g., a public key, a unitidentifier), information regarding key generation (e.g., basis, method),and/or a pseudo random function (e.g., random number generator). Theunique key set includes one or more keys for encrypting one or moreencoded data slices of a corresponding chunkset for a DST execution unit396.

As a specific example, the encrypt module 402 generates the unique keysets based on the assigned partial tasks. For a given DST EX unit, theencrypt module 402 identifies the assigned partial task 414 and performsa deterministic mathematical function (e.g., a hashing function, ahash-based message authentication code function, a mask generatingfunction, a sponge function) on bits of the assigned partial task tocreate a value. The encrypt module 402 manipulates the value into theunique key set (e.g., set equal to, use as a seed for multiple uniquekeys, use as a value in a formula, truncate, use the mask generatingfunction).

After generating the unique key sets, the encrypt module 402 encryptseach of the chunksets of slices 410 with a corresponding one of theunique key sets to produce chunksets of encrypted slices 416. Theencrypt module 402 provides the chunkset of encrypted slices 416 to theoutput module 404, which sends respective sub-chunksets of encryptedslices 416 and respective assigned partial tasks 418 to the DST EX unitsof the primary set 392. In addition, the output module 404 sendsrespective sub-chunksets of redundancy slices 412 to the DST EX units ofthe redundancy set 394.

FIG. 42C is a flowchart illustrating an example of encrypting slices.The method begins at step 420 where a processing module (e.g., of adistributed storage and task (DST) processing unit) encodes data using adispersed storage error encoding function to produce a plurality of setsof encoded data slices, where a set of the plurality of sets of encodeddata slices includes encoded data slices (e.g., a decode thresholdnumber) and redundancy encoded data slices. The encoded data slices ofthe plurality of sets of encoded data slices are arranged into chunksetsof slices (e.g., by common pillar) and the redundancy encoded dataslices of the plurality of sets of encoded data slices are arranged intochunksets of redundancy slices. The method continues at step 422 wherethe processing module selects a set of primary storage and executionunits for the chunksets of slices and a set of redundancy storage andexecution units for the chunksets of redundancy slices. The methodcontinues at step 424 where the processing module assigns partial tasksof one or more distributed computing tasks to the set of primary storageand execution units.

The method continues at step 426 where the processing module generates aunique key set for each of the primary storage and execution units basedon at least one of: the assigned partial task for the correspondingprimary storage and execution unit, information regarding thecorresponding primary storage and execution unit, information regardingkey generation, and a pseudo random function. The generating the uniquekey set for one of the primary storage and execution units includes avariety of generating approaches. A first generating approach includesgenerating a unique key that is used to encrypt the slices of thecorresponding chunkset of encrypted slices. A second generating approachincludes generating multiple unique keys, where one of the multipleunique keys is used to encrypt one or more slices of the correspondingchunkset of encrypted slices. A third generating approach includes aseries of generating steps. A first generating step of the thirdgenerating approach includes identifying the assigned partial task forthe one of the primary storage and execution units. A second generatingstep of the third generating approach includes performing adeterministic mathematical function on bits of the assigned partial taskto create a value. A third generating step of the third generatingapproach includes manipulating the value into the unique key set. Afourth generating approach includes ascertaining a public key of apublic/private key pair for the one of the primary storage and executionunits and utilizing the public key to generate the unique key set.

The method continues at step 428 where the processing module encryptseach of the chunksets of slices with a corresponding one of the uniquekey sets to produce chunksets of encrypted slices. The method continuesat step 430 where the processing module sends the chunksets of encryptedslices and an indication of the assigned partial tasks to the set ofprimary storage and execution units for storage of the chunksets ofencrypted slices and execution of the assigned partial tasks on thechunksets of encrypted slices. The indication of the assigned partialtask for one of the set of primary storage and execution units includesat least one of an indication that the assigned partial task was used togenerate the corresponding unique key set and an indication as to howthe assigned partial task was used to generate the corresponding uniquekey set. The indication of the assigned partial task for one of the setof primary storage and execution units further includes sending acorresponding assigned partial task to the one of the set of primarystorage and execution units. The method continues at step 432 where theprocessing module sends the chunksets of redundancy slices to the set ofredundancy storage and execution units for storage therein.

FIG. 42D is a schematic block diagram illustrating another embodiment ofa distributed storage and task (DST) execution unit 1, of a set of DSTexecution units, that includes a slice memory 440, a chunk 1 decryptor,a distributed task (DT) execution module 90, a key memory 442, a chunk 1key set decryptor, and a computing task queue 444 (e.g., implementedwithin a memory device). The DST execution unit 1 functions to receiveencrypted chunk 1 slices, decrypt the encrypted chunk 1 slices toproduce chunk 1 slices, perform partial tasks 446 on the chunk 1 slicesto produce partial results 448, and output the partial results 448. Theslice memory four and 40 temporarily stores the encrypted chunk 1slices. The key memory 442 temporarily stores a received encrypted keyset 1. The computing task queue 444 temporarily stores received partialtasks 446 associated with the encrypted chunk 1 slices.

The chunk 1 key set decryptor decrypts the encrypted key set 1 toproduce a key set 1. The chunk 1 key set decryptor decrypts theencrypted key set 1 as a whole when the encrypted key set 1 was producedas a whole. The chunk 1 key set decryptor decrypts a plurality ofencryption keys when the encrypted key set 1 was produced as a pluralityof encryption keys. The decrypting includes decrypting the encrypted keyset 1 utilizing a private of a public/private key pair associated withthe DST execution unit 1. Alternatively, the decrypting includesdecrypting the encrypted key set 1 utilizing a public-key of anotherpublic/private key pair associated with a sending entity (e.g., a keygenerator).

The chunk 1 decryptor decrypts the encrypted chunk 1 slices utilizing atleast one encryption key of the key set 1 to produce the chunk 1 slices.The decrypting includes decrypting each encrypted chunk 1 slice with acommon encryption key of the key set 1 and decrypting each encryptedchunk 1 slice with a corresponding unique encryption key of the keyset 1. The DT execution module 90 executes at least one partial task ofthe partial tasks 446 on one or more chunk 1 slices of the chunk 1slices to produce the partial results 448. The chunk 1 key set decryptormay issue a key delete 450 message to the key memory 442 to delete theencrypted key set 1 when the encrypted chunk 1 slices have beensuccessfully decrypted.

FIG. 42E is a flowchart illustrating an example of decrypting slices.The method begins at step 452 where a processing module (e.g., of adistributed storage and task (DST) execution unit) obtains a chunk ofencrypted chunk slices, where the chunk includes one or more slices. Theobtaining includes at least one of receiving and retrieving. Forexample, the processing module receives the chunk in a distributedcomputing request that includes one or more of the chunk, an encryptedkey set, and associate partial tasks. The method continues at step 454where the processing module obtains the encrypted key set. The obtainingincludes at least one of retrieving and receiving. The method continuesat step 456 where the processing module decrypts the encrypted key setto produce a key set. The decrypting includes at least one of utilizinga public-key of a private/public key pair of a sending entity thatprovided the encrypted key set, utilizing a stored master key, andutilizing a private key of another private/public key pair associatedwith the processing module. The decrypting includes decrypting theencrypted key set as a whole and decrypting individual encryption keysof the encrypted key set to produce the key set.

The method continues at step 458 where the processing module decryptsthe encrypted chunk slices utilizing the key set to produce a chunk ofchunk slices. The decrypting includes decrypting all encrypted chunkslices with a common encryption key of the key set and decrypting eachencrypted chunk slice with a unique encryption key of the key set. Themethod continues at step 460 where the processing module deletes atleast one of the encrypted key set and the key set. The method continuesat the step where the processing module obtains the partial tasks. Theobtaining includes at least one of retrieving and receiving. The methodcontinues at step 464 where the processing module executes the partialtasks on the chunk of chunk slices to produce partial results.

FIG. 43A is a schematic block diagram of another embodiment of adistributed computing system that includes a distributed storage (DS)error encoding 466, a key generator 468, a decode threshold number ofchunk encryptors (e.g., chunks 1-3), a decode threshold number ofadditional DS error encodings 1-3, a decode threshold number ofdispersed storage and task (DST) execution unit storage sets 1-3, and aset of DST execution units 1-4. For example, the set of DST executionunits includes four units when a pillar width is four.

The system functions to receive a data chunkset 470 and store the datachunkset 470 as a decode threshold number of encrypted chunk slices perchunk in a decode threshold number of DST execution units 1-3 of the setof DST execution units 1-4. The data chunkset 470 includes a decodethreshold number of chunks. For each chunk of the decode thresholdnumber of chunks, the DS error encoding 466 encodes the chunk to produceone or more chunk slices. For example, the DS error encoding 466 encodeschunk 1 to produce one or more chunk 1 slices. For each decode thresholdnumber of chunk slices, the DS error encoding 466 encodes the decodethreshold number of chunk slices to produce at least one correspondingerror coded slice in accordance with a dispersed storage error codingfunction. For example, the DS error encoding 466 encodes a decodethreshold number of chunk slices that includes a slice two of the chunk1 slices, a slice two of the chunk 2 slices, and a slice two of thechunk 3 slices to produce an error coded slice two (e.g. of pillar 4).The DS error encoding 466 stores the at least one corresponding pillar 4error coded slice in a corresponding at least one DST execution unit 4associated with storing error coded slices of the set of DST executionunits 1-4.

The key generator 468 generates keys 472 for encrypting chunk slices toproduce encrypted chunk slices. The keys 472 includes a decode thresholdnumber of key sets 1-3 utilized to encrypt the chunk slices. Forexample, the chunk 1 encryptor utilizes key set 1 to encrypt chunk 1slices to produce encrypted chunk 1 slices etc. A key set includes oneor more encryption keys. For example, the key set includes oneencryption key when a common encryption key is desired for the one morechunk slices. As another example, the key set includes, for each chunkslice of the one or more chunk slices, a corresponding encryption keywhen a unique encryption key is desired for each of the one or morechunk slices. The generating of an encryption key of the one or moreencryption keys may be based on one or more of a random number, a slicename, a lookup, receiving the key, and performing a deterministicfunction operation on a slice name.

The other DS error encodings 1-3 encode each key set of the decodethreshold number of key sets 1-3 to produce a decode threshold number ofkey set 1-3 slices utilizing a dispersed storage error coding function.For example, DS error encoding 1 encodes key set 1 to produce at leastone set of key set 1 slices, etc. Each DS error encoding of the other DSerror encodings 1-3 facilitates storage of associated key set slices ina corresponding DST execution unit storage set of the decode thresholdnumber of DST execution unit storage sets 1-3. For example, DS errorencoding 2 facilitates storage of key set 2 slices in DST execution unitstorage set 2. Each DST execution unit storage set of the decodethreshold number of DST execution unit storage sets 1-3 outputsassociated key set slices to a corresponding DST execution unit of thedecode threshold number of DST execution units 1-3. For example, DSTexecution unit storage set 3 outputs at least one set of key set 3slices to DST execution unit 3 of the decode threshold number of DSTexecution units 1-3.

The decode threshold number of chunk encryptors 1-3 encryptcorresponding chunk slices 1-3 utilizing associated decode thresholdnumber of key sets 1-3 to produce encrypted chunk slices 1-3. The decodethreshold number of chunk encryptors 1-3 outputs the encrypted chunkslices 1-3 to the corresponding decode threshold number of DST executionunits 1-3 for storage therein. In addition, at least one of the DS errorencoding 466, the key generator 468, and the decode threshold number ofchunk encryptors outputs slice names associated with the encrypted chunkslices 1-3 and partial tasks to the decode threshold number of DSTexecution units 1-3.

FIG. 43B is a flowchart illustrating another example of encryptingslices. The method begins at step 474 where a processing module (e.g.,of a distributed storage and task (DST) client module) partitions achunkset of data to produce a decode threshold number of chunks, whereeach chunk includes one or more slices. The method continues at step 476where the processing module encodes the decode threshold number ofchunks utilizing a dispersed storage error coding function in accordancewith processing parameters to produce at least one group of error codedslices. The method continues at step 478 where the processing modulegenerates a key set for each chunk of the decode threshold number ofchunks. The method continues at step 480 where the processing moduleencrypts each chunk of the decode threshold number of chunks utilizing acorresponding key set to produce encrypted chunk slices.

For each chunk of the decode threshold number of chunks, the methodcontinues at step 482 where the processing module outputs correspondingencrypted chunk slices to a corresponding DST execution unit. Theoutputting may further include outputting corresponding chunk slicenames and associated partial tasks. For each chunk of the decodethreshold number of chunks, the method continues at step 484 where theprocessing module encodes the key set utilizing the dispersed storageerror coding function to produce at least one set of key set slices. Foreach key set, the method continues at step 486 where the processingmodule outputs the associated key set slices to a corresponding DSTexecution unit storage set for storage therein. For each group of the atleast one group of error coded slices, the method continues at step 488where the processing module outputs the error coded slices to acorresponding DST execution unit associated with the storage of errorcoded slices for storage therein

FIG. 43C is a schematic block diagram illustrating another embodiment ofa distributed storage and task (DST) execution unit 1, of a set of DSTexecution units 1-n, that includes a slice memory 490, a chunk 1decryptor, a distributed task (DT) execution module 90, a distributedstorage (DS) error decoding 492, and a computing task queue 494 (e.g.,implemented using a memory device). The DST execution unit 1 functionsto receive encrypted chunk 1 slices, decrypt the encrypted chunk 1slices to produce chunk 1 slices, perform partial tasks 496 on the chunk1 slices to produce partial results 498, and output the partial results498. The slice memory 490 temporarily stores the encrypted chunk 1slices and at least one set of key set 1 slices associated with theencrypted chunk 1 slices. The computing task queue 494 temporarilystores received partial tasks 496 associated with the encrypted chunk 1slices.

The DT execution module 90 interprets partial tasks 496 to identifyrequired chunk 1 slices and associated required key set 1 slices (e.g.,matching slice names). The DT execution module 90 generates key set 1slice requests that includes identity of the associated required key set1 slices and outputs the key set 1 slice requests (e.g., to acorresponding DST execution unit storage set). In response, the key set1 slices are received and stored in the slice memory 490. The DS errordecoding 492 decodes the at least one set of key set 1 slices utilizinga dispersed storage error coding function to produce a key set 1. Thechunk 1 decryptor decrypts the encrypted chunk 1 slices utilizing atleast one encryption key of the key set 1 to produce the chunk 1 slices.The decrypting includes decrypting each encrypted chunk 1 slice with acommon encryption key of the key set 1 and decrypting each encryptedchunk 1 slice with a corresponding unique encryption key of the keyset 1. The DT execution module 90 executes at least one partial task ofthe partial tasks 496 on one or more chunk 1 slices of the chunk 1slices to produce the partial results 498.

FIG. 43D is a flowchart illustrating another example of decryptingslices, that includes similar steps to a FIG. 42E. The method beginswith step 452 of FIG. 42E where a processing module (e.g., of adistributed storage and task (DST) execution unit) obtains a chunk ofencrypted chunk slices, where the chunk includes one or more slices. Themethod continues at step 500 where the processing module generates atleast one set of key set slice requests. The generating includes atleast one of interpreting associated partial task requests to produceany key set identifier for inclusion in the at least one set of key setslice requests. The method continues at step 502 where the processingmodule outputs the at least one set of key set slice requests to a DSTexecution unit storage set corresponding to a key set slice vault. Theoutputting includes identifying the DST execution unit storage set basedon at least one of a lookup, receiving a DST execution unit storage setidentifier, and receiving internet protocol addresses of a set of DSTexecution units of the DST execution unit storage set.

The method continues at step 504 where the processing module receiveskey set slices (e.g., from the DST execution unit storage set). Themethod continues at step 506 where the processing module decodes the keyset slices utilizing a dispersed storage error coding function toreproduce a key set. The method continues with step 458 of FIG. 42Ewhere the processing module decrypts the encrypted chunk slicesutilizing the key set to produce a chunk of chunk slices. The methodcontinues at step 508 where the processing module facilitates deletionof the key set. The method continues with step 462 and 464 of FIG. 42Ewhere the processing module obtains partial tasks and executes thepartial tasks on the chunk of chunk slices to produce partial results.

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage (DS) error module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, an encryption engine 509,an error encoding module 146, a slicing module 148, and a per slicesecurity processing module 150. Each of these modules is coupled to acontrol module 116 to receive control information 160 therefrom.Alternatively, the control module 116 may be omitted and each modulestores its own parameters.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segment processing module 142 segments the datapartition 120 into data segments 152 based on the segmentinginformation. For example, the segmenting information indicates how manyrows to segment the data based on a decode threshold of an errorencoding scheme, indicates how many columns to segment the data intobased on a number and size of data blocks within the data partition 120,and/or indicates how many columns to include in a data segment 152

The encryption engine 509 secures the data segments 152 to producesecured segments 154 based on segment security information andpartitioning information received as control information 160 from thecontrol module 116. The segment security information includes one ormore of data compression, encryption, watermarking, integrity check(e.g., cyclic redundancy check (CRC), etc.), and/or any other type ofdigital security. The partitioning information includes one or more ofdata sub-segment partitioning instructions, a master key, a sub-keygeneration approach indicator, a deterministic function type indicator,a master key generation instruction indicator, a decode thresholdnumber, and one or more shared secrets corresponding to one or moredistributed storage and task execution modules. For example, theencryption module 509 partitions a data segment 152 into a decodethreshold number of data sub-segments. The encryption module thengenerates a unique key for encrypting the data sub-segments and encryptseach of the data sub-segments using a corresponding unique key toproduce a decode threshold number of encrypted data sub-segments. Theencryption module then combines the decode threshold number of encrypteddata sub-segments to produce encrypted data as a secured segment 154.When the encryption engine 509 is not enabled, it passes the datasegments 152 to the error encoding module 146 or is bypassed such thatthe data segments 152 are provided to the error encoding module 146. Theencryption module 509 is discussed in greater decode with reference toFIG. 44B.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters of controlinformation 160 to produce encoded data 156.

The error correction encoding parameters (e.g., also referred to asdispersed storage error coding parameters) include identifying an errorcorrection encoding scheme (e.g., forward error correction algorithm, aReed-Salomon based algorithm, an online coding algorithm, an informationdispersal algorithm, etc.), a pillar width, a decode threshold, a readthreshold, a write threshold, etc. The error encoding module 146 mayreceive at least some of the error correction encoding parameters fromthe encryption engine 509. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree when the encryption engine 509 produces three data sub-segmentsfrom the data segment 152.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parameters of thecontrol information 160 to produce sliced encoded data 158. As such, fordata segments 156 of a data partition 120, the slicing module 140outputs a plurality of sets of encoded data slices 158. For example, ifthe pillar width is five, the slicing module 148 slices the encoded datasegments 156 into sets of five encoded data slices.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information of the control information 160 to produce encodeddata slices per data partition 122. The slice security informationincludes data compression, encryption, watermarking, integrity check(e.g., CRC, etc.), and/or any other type of digital security. When theper slice security processing module 150 is not enabled, it passes theencoded data slices 158 or is bypassed such that the slice encoded data158 are outputted as the encoded data slices per data partition.

FIG. 44B is a schematic block diagram of an embodiment of an encryptionengine 509 that includes a partition function 510, a key generator 512,n number of encryptors 514, n number of sub-key generators 516, anaggregator 518, a deterministic function 520, a masked key generator522, and a combiner 524. The encryption engine 509 receives datasegments 152, processes the data segments 152 to produce securedsegments 154, and outputs the secured segments 154 to an error encodingmodule 146, where the error encoding module 146 dispersed storage errorencodes each of the secured segments 154 to produce a set of encodeddata slices 156 for storage in at least one of a dispersed storagenetwork system and a distributed storage and task network module.

The encryption engine 509 functions to encrypt the data segments 152 toproduce secured segments 154 such that the secured segments 154 may beencoded using the dispersed storage error coding function to producesets of encoded data slices 156 for storage and further processing(e.g., distributed computing of one or more partial tasks on at leastsome of the encoded data slices 156 in a dispersed storage and tasknetwork (DSTN) module). The partition function 510 partitions each datasegment 152 into n data sub-segments 1-n in accordance with a datapartitioning approach. The data partitioning approach includes at leastone of partitioning the data segment 152 into a decode threshold numberof data sub-segments and partitioning the data segment 152 such that atleast one data sub-segment includes a data record associated with adistributed computing partial task. The partition function 510 isfurther operable to generate n descriptors 1-n (e.g., data sub-segmentidentifier (ID)) for the n data sub-segments 1-n. Each descriptor ofdescriptors 1-n may include one or more of a source name, a data segmentID, a data type indicator, a data size indicator, a data contentindicator, a data source owner identifier, and a slice name.

The key generator 512 generates a master key 532 based on at least oneof a random number, performing a deterministic function on a DSTNaddress, performing a deterministic function on a timestamp, a lookup,and receiving the master key 532. For example, the key generatorgenerates a random key to produce the master key 532. Each sub-keygenerator 516 of the n sub-key generators 516 generates a sub-key ofsub-keys 1-n based on the master key 532 and associated descriptor ofdescriptors 1-n. For example, a first sub-key generator 516 utilizes themaster key 532 and descriptor 1 to generate a sub-key 1. The generatingincludes performing a deterministic function on one or more of themaster key 532 and the associated descriptor to generate the sub-key.The deterministic function including at least one of a hashing function(e.g., message digest algorithm 5 (MD5)), a mask generating function(MGF), a hash-based message authentication code (HMAC), and a spongefunction. The generating may further include truncating a result of theperforming of the deterministic function to provide a desired key lengthfor the sub-key.

Each encryptor 514 of the n encryptors 514 encrypts an associated datasub-segment of the n data-segments 1-n utilizing a corresponding sub-keyof the n sub-keys 1-n to produce an associated encrypted datasub-segment of n encrypted data sub-segments 1-n. For example, a secondencryptor 514 encrypts data sub-segment 2 utilizing a sub-key 2 toproduce encrypted data sub-segment 2. The aggregator 518 aggregates then encrypted data sub-segments 1-n to produce encrypted data 534. Forexample, the aggregator 518 sequentially aggregates encrypted datasub-segment 1 through encrypted data sub-segment n to produce theencrypted data 534. The deterministic function 520 performs adeterministic function (e.g., same or different as utilized by thesub-key generators 516) on the encrypted data 534 to produce transformeddata 536. The performing of the deterministic function may furtherinclude truncating an interim result of the deterministic function toprovide a desired bit length of the transformed data 536 tosubstantially match a length of the master key 532.

The masked key generator 522 masks the master key 532 utilizing thetransformed data 536 to produce a masked key 538. The masking mayinclude at least one of a mathematical function and a logical function.For example, the masked key generator 522 performs an exclusive ORlogical function on the master key 532 and the transformed data 536 toproduce the masked key 538. The combiner 524 combines the encrypted data534 and the masked key 538 to produce the secured segment 154. Thecombining includes at least one of appending the masked key 538 to theencrypted data 534, appending the encrypted data 534 to the masked key538, and interleaving the masked key 538 and the encrypted data 534 toproduce the secured segment 154.

The encryption engine 509 outputs the secured segments 154 to the errorencoding module 146. The error encoding module 146 encodes the eachsecured segment 154 utilizing the dispersed storage error codingfunction to produce the encoded data slices 156. Each set of encodeddata slices 156 may include a decode threshold number of slices that aresubstantially the same as the n encrypted data partitions 1-n (e.g.,combined with the masked key 538) when the error encoding module 146utilizes an encoding matrix that includes a unity matrix as a firstdecode threshold number of rows and the decode threshold number issubstantially the same as the value n. The set of encoded data slices156 may further include a pillar width minus the decode threshold numberof error coded slices corresponding to remaining rows of the encodingmatrix (e.g., redundancy encoded data slices to facilitate data segmentrecovery).

FIG. 44C is a schematic block diagram of another embodiment of adistributed computing system that includes a computing device 540 and adistributed storage and task (DST) execution unit set 542. The DSTexecution unit set 542 includes a set of DST execution units 544.Alternatively, one or more of the DST execution units 544 may beimplemented utilizing one or more of a server, a storage unit, a userdevice, a DST processing unit, a dispersed storage (DS) processing unit,and a DS unit. The computing device 540 may be implemented utilizing atleast one of a DST processing unit, a DS processing unit, a user device,a DST execution unit, and a DS unit. For example, the computing device540 is implemented as the DST processing unit. The computing device 540includes a DS module 546. The DS module 546 includes a sub-segmentingmodule 548, an encryption module 550, a combining module 552, and anencoding module 554.

The system functions to store a data partition 556 in the DST executionunit set 542. The storing includes four primary functions where a firstprimary function includes sub-segmenting the data partition 556 toproduce a set of data sub-segments 558, a second primary functionincludes encrypting the set of data sub-segments 558 to produceencrypted data 560 and a masked key 562, a third primary functionincludes combining the encrypted data 560 and the masked key 562 toproduce an encrypted data segment 564, and a fourth primary functionincludes encoding the encrypted data segment 564 to produce a set ofencoded data slices 566 for storage in the DST execution unit set 542.

The first primary function to sub-segment the data partition 556 toproduce the set of data sub-segments 558 includes a series ofsub-segmenting steps. In a first sub-segmenting step, the sub-segmentingmodule 548 segments the data partition 556 into a plurality of datasegments. For a data segment of the plurality of data segments, in asecond sub-segmenting step, the sub-segmenting module 548 divides thedata segment into the set of data sub-segments 558. The sub-segmentingmodule 548 may divide the data segment into the set of data sub-segments558 based a decode threshold number of a dispersed storage errorencoding function. For example, the sub-segmenting module 548 dividesthe data segment into a decode threshold number of data sub-segments558.

The second primary function to encrypt the set of data sub-segments 558to produce the encrypted data 560 and the masked key 562 includes aseries of encrypting steps. In a first encrypting step, the encryptionmodule 550, for the data segment of the plurality data segments,generates a set of sub keys for the set of data sub-segments 558 basedon a master key. The encryption module 550 may obtain the master keybased on at least one of a random number, performing a deterministicfunction on a dispersed storage network address, performing adeterministic function on a timestamp, performing a lookup, andreceiving the master key. For example, the encryption module 550generates a random key as the master key. Alternatively, the encryptionmodule 550 obtains a first master key for a first data segment of theplurality of data segments and obtains a second master key for a seconddata segment of the plurality of data segments.

The encryption module 550 generates the set of sub keys by one of avariety of generating approaches. A first generating approach includes aseries of generating steps. In a first generating step, the encryptionmodule 550 generates a first sub key of the set of sub keys byperforming a deterministic function on the master key and a descriptorof a first data sub-segment of the set of data sub-segments 558. Thedescriptor of the first data sub-segment includes at least one of anidentifier of the first sub-segment, a data type of the first datasub-segment, a data content indicator of the first data sub-segment, anda data size of the first data sub-segment. The deterministic functionincludes at least one of a logical function, a truncation function, ahashing function, a hash-based message authentication code function, amask generating function, and a sponge function. For example, theencryption module performs an exclusive OR function on the master keyand the descriptor of the first data sub-segment to produce the firstsub key. In a second generating step, the encryption module 550generates a second sub key of the set of sub keys by performing thedeterministic function on the master key and a descriptor of a seconddata sub-segment of the set of data sub-segments.

A second generating approach includes a series of alternate generatingsteps. In a first alternate generating step, the encryption module 550generates the first sub key of the set of sub keys by performing afunction on the master key, the descriptor of the first data sub-segmentof the set of data sub-segments 558, and a first shared secret. Thefunction includes at least one of a mathematical function, a logicalfunction, and the deterministic function. For example, the encryptionmodule 558 performs the exclusive OR logical function on the master key,the descriptor of the first data sub-segment and the first shared secretto produce the first sub key. The encryption module 550 may obtain thefirst shared secret by performing a shared secret generation algorithmwith an associated DST execution unit 544 of the DST execution unit set542. In a second alternate generating step, the encryption module 550generates the second sub key of the set of sub keys by performing thefunction on the master key, the descriptor of the second datasub-segment of the set of data sub-segments 558 is, and a second sharedsecret.

In a second encrypting step of the series of encrypting steps, theencryption module 550 encrypts the set of data sub-segments 558 usingthe set of sub keys to produce a set of encrypted data sub-segments. Ina third encrypting step, the encryption module 550 aggregates the set ofencrypted data sub-segments into the encrypted data 560. For example,the encryption module 550 arranges the set of encrypted datasub-segments in order of the set of data sub-segments 558 to produce theencrypted data 560. In a fourth encrypting step, the encryption module550 generates the masked key 562 based on the encrypted data 560 and themaster key. The encryption module 550 generates the masked key byperforming another deterministic function on the encrypted data 560 toproduce transformed data and performing a masking function on the masterkey using the transformed data and to produce the masked key 562. Themasking function includes at least one of a logical function, amathematical function, and the deterministic function. For example, theencryption module 550 performs the mask generating function on theencrypted data 560 to produce the transformed data to include a numberof bits substantially the same as the master key and performs theexclusive OR function on the master key and the transformed data toproduce the masked key 562.

The third primary function to combine the encrypted data 560 and themasked key 562 to produce the encrypted data segment 564 includes, forthe data segment of the plurality data segments, the combining module552 combining the encrypted data 560 and the masked key 562 to producethe encrypted data segment 564. The combining module 552 combines theencrypted data 560 and the masked key 562 by at least one of a varietyof combining approaches. In a first combining approach, the combiningmodule 552 interleaves the masked key 562 with the encrypted data 560 toproduce the encrypted data segment 564. In a second combining approach,the combining module 552 appends the masked key 562 to the encrypteddata 560 to produce the encrypted data segment 564. In a third combiningapproach, the combining module 552 distributes, in accordance with apattern, portions of the masked key 562 within the encrypted data 560 toproduce the encrypted data segment 564. The distributing includes usingsome known pattern of the encrypted data. For example, the combiningmodule 552 distributes one byte of the masked key 562 for every 100Kbytes of the encrypted data 560.

The fourth primary function to encode the encrypted data segment 564 toproduce the set of encoded data slices 566 for storage in the DSTexecution unit 542 includes a series of encoding steps. In a firstencoding step, the encoding module 554 encodes the encrypted datasegment 564 in accordance with the dispersed storage error encodingfunction to produce the set of encode data slices 566. In a secondencoding step, the encoding module 556 sends the set of encoded dataslices 566 to the DST execution unit set 542 where the DST executionunit set 542 stores the set of encoded data slices 566 and may furtherperform one or more partial tasks on at least some of the encoded dataslices corresponding to the encrypted data 560 to produce partialresults.

For another data segment of the plurality of data segments, thesub-segmenting module 548 divides the other data segment into a secondset of data sub-segments. The encryption module 550 generates a secondset of sub keys for the second set of data sub-segments based on themaster key and encrypts the second set of data sub-segments using thesecond set of sub keys to produce a second set of encrypted datasub-segments. The encryption module 550 aggregates the second set ofencrypted data sub-segments into second encrypted data and generates asecond masked key based on the second encrypted data and the master key.The combining module 552 combines the second encrypted data and thesecond masked key to produce a second encrypted data segment forencoding and storing in the DST execution unit set 542. The encryptionmodule 552 may generate a first slice group from a first encrypted datasub-segment of the encrypted data segment and a first encrypted datasub-segment of the second encrypted data segment. The encryption module552 may further generate a second slice group from a second encrypteddata sub-segment of the encrypted data segment and a second encrypteddata sub-segment of the second encrypted data segment.

FIG. 44D is a flowchart illustrating an example of encoding slices. Themethod begins at step 570 where a processing module (e.g., a dispersedstorage (DS) processing module) segments a data partition into aplurality of data segments. For a first data segment of the pluralitydata segments, the method continues at step 572 where the processingmodule divides data segment into a set of data sub-segments. Thedividing the data segment into the set of data sub-segments may be baseda decode threshold of a dispersed storage error encoding function. Forexample, the processing module divides the data segment into a decodethreshold number of data sub-segments.

The method continues at step 574 where the processing module generates aset of sub keys for the set of data sub-segments based on a master key.The processing module may obtain the master key as at least one of afirst master key for a first data segment of the plurality of datasegments and a common master key for the first data segment andsubsequent data segments of the plurality of data segments. Thegenerating the set of sub keys includes a variety of key generatingapproaches. A first key generating approach includes a series of keygenerating steps. In a first key generating step, the processing modulegenerates a first sub key of the set of sub keys by performing adeterministic function on the master key and a descriptor of a firstdata sub-segment of the set of data sub-segments. The descriptor of thefirst data sub-segment includes at least one of an identifier of thefirst sub-segment, a data type of the first data sub-segment, a datacontent indicator of the first data sub-segment, and a data size of thefirst data sub-segment. In a second key generating step, the processingmodule generates a second sub key of the set of sub keys by performingthe deterministic function on the master key and a descriptor of asecond data sub-segment of the set of data sub-segments. A second keygenerating approach includes a series of alternate key generating steps.In a first alternate key generating step, the processing modulegenerates the first sub key of the set of sub keys by performing afunction on the master key, a descriptor of a first data sub-segment ofthe set of data sub-segments, and a first shared secret. In a secondalternate key generating step, the processing module generates thesecond sub key of the set of sub keys by performing the function on themaster key, a descriptor of a second data sub-segment of the set of datasub-segments, and a second shared secret. The method continues at step576 where the processing module encrypts the set of data sub-segmentsusing the set of sub keys to produce a set of encrypted datasub-segments. The method continues at step 578 where the processingmodule aggregates the set of encrypted data sub-segments into encrypteddata. The method continues at step 580 where the processing modulegenerates a masked key based on the encrypted data and the master key.The generating of the masked key includes performing anotherdeterministic function on the encrypted data to produce transformed dataand performing a masking function on the master key using thetransformed data and to produce the masked key.

The method continues at step 582 where the processing module combinesthe encrypted data and the masked key to produce an encrypted datasegment. The combining of the encrypted data and the masked key includesat least one of a variety of combining approaches. In a first combiningapproach, the processing module interleaves the masked key with theencrypted data to produce the encrypted data segment. In a secondcombining approach, the processing module appends the masked key to theencrypted data to produce the encrypted data segment. In a thirdcombining approach, the processing module distributes, in accordancewith a pattern, portions of the masked key within the encrypted data toproduce the encrypted data segment. The distributing includes using someknown pattern of the encrypted data (e.g., insert one byte of the maskedkey for every 100 Kbytes of encrypted data). The method continues atstep 584 where the processing module encodes the encrypted data segmentin accordance with the dispersed storage error encoding function toproduce a set of encode data slices for storage in a dispersed storagenetwork.

For a second (e.g., another) data segment of the plurality of datasegments, the method continues at step 586 where the processing moduledivides the second data segment into a second set of data sub-segments.The method continues at step 588 where the processing module generates asecond set of sub keys for the second set of data sub-segments based onthe master key. Alternatively, the processing module obtains a secondmaster key for the second data segment of the plurality of datasegments. The method continues at step 590 where the processing moduleencrypts the second set of data sub-segments using the second set of subkeys to produce a second set of encrypted data sub-segments. The methodcontinues at step 592 where the processing module aggregates the secondset of encrypted data sub-segments into second encrypted data. Themethod continues at step 594 where the processing module generates asecond masked key based on the second encrypted data and the master key.The method continues at step 596 where the processing module combinesthe second encrypted data and the second masked key to produce a secondencrypted data segment. The method continues at step 598 where theprocessing module generates a first slice group from a first encrypteddata sub-segment of the encrypted data segment and a first encrypteddata sub-segment of the second encrypted data segment and generates asecond slice group from a second encrypted data sub-segment of theencrypted data segment and a second encrypted data sub-segment of thesecond encrypted data segment.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage (DS) error decoding module 182 of an inbounddistributed storage and task (DST) processing section. The DS errordecoding module 182 includes an inverse per slice security processingmodule 202, a de-slicing module 204, an error decoding module 206, adecryption engine 600, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice for a partition 122 based on slice de-securityinformation received as control information 190 (e.g., the compliment ofthe slice security information discussed with reference to FIG. 44A)received from the control module 186. The slice security informationincludes data decompression, decryption, de-watermarking, integritycheck (e.g., CRC verification, etc.), and/or any other type of digitalsecurity. For example, when the inverse per slice security processingmodule 202 is enabled, it verifies integrity information (e.g., a CRCvalue) of each encoded data slice of retrieve slices for a partition122, it decrypts each verified encoded data slice, and decompresses eachdecrypted encoded data slice to produce slice encoded data 158. When theinverse per slice security processing module 202 is not enabled, itpasses the encoded data slices 122 as the sliced encoded data 158 or isbypassed such that the retrieved encoded data slices 122 are provided asthe sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Salomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The decryption engine 600, when enabled by the control module 186,unsecures the secured data segments 154 based on segment securityinformation and partitioning information received as control information190 from the control module 186. The segment security informationincludes data decompression, decryption, de-watermarking, integritycheck (e.g., CRC, etc.) verification, and/or any other type of digitalsecurity. The partitioning information includes one or more of datasub-segment de-partitioning instructions, a master key, a sub-keygeneration approach indicator, a deterministic function type indicator,a master key generation instruction indicator, a decode thresholdnumber, and shared secrets corresponding to one or more distributedstorage and task execution modules. For example, when the decryptionengine 600 is enabled, it de-combines a secured segments 154 to produceencrypted data, de-aggregates the encrypted data to produce a pluralityof encrypted data sub-segments, decrypts the plurality of encrypted datasub-segments to produce a plurality of data sub-segments, andde-partitions the plurality of data sub-segments to produce datasegments 152. In addition, the decryption engine 600 may issue one ormore sub-keys to one or more corresponding DST execution units tofacilitate decrypting corresponding locally stored slices as theencrypted data sub-segments to produce the data sub-segments for partialtask execution. When the decryption engine 600 is not enabled, it passesthe decoded data segment 154 as the data segment 152 or is bypassed. Thede-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 45B is a schematic block diagram of an embodiment of a decryptionengine 600 that includes a de-partition function 610, n number ofdecryptors 608, n number of sub-key generators 516, a de-aggregator 606,a deterministic function 520, a de-masking function 504, and ade-combiner 602. The decryption engine 600 receives secured segments 154from an error decoding 206 and decrypts the secured segments 154 toproduce data segments 152. The error decoding 206 decodes encoded data156 using a dispersed storage error coding function to produce thesecured segments 154. For each secured segment 154, the decryptionengine 600 produces n sub-keys based on the secured segment 154. Thedecryption engine 600 sends the n sub-keys to n number of distributedstorage and task (DST) execution units. Each DST execution unit includesthe decryptor 608 and a distributed task (DT) execution module 90. Thedecryptors 608 of the n DST execution units 1-n each obtains a slice ofn slices (e.g., retrieved from a local memory) and decrypts the slice toproduce a data sub-segment of n data sub-segments 1-n for furtherpartial task processing to produce partial results of n partial results1-n.

The de-combiner 602 de-combines the secured segment 154 to reproduceencrypted data 534 and a masked key 538 in accordance with ade-combining approach. The de-combining approach includes at least oneof de-interleaving and de-appending. The deterministic function 520performs a deterministic function on the encrypted data 534 to producetransformed data 536. The deterministic function includes at least oneof a hashing function, a mask generating function (MGF), a hash-basedmessage authentication code (HMAC), and a sponge function. Theperforming of the deterministic function may include truncating aninterim result of the deterministic function to provide a desired bitlength of the transformed data 536.

The de-masking function 604 de-masks the masked key 538 utilizing thetransformed data 536 to reproduce a master key 532. The de-masking mayinclude at least one of a mathematical function and a logical function.For example, the de-masking function performs an exclusive OR logicalfunction on the masked key 538 and the transformed data 536 to reproducethe master key 532. The de-aggregator 606 de-aggregates the encrypteddata 534 into n encrypted data sub-segments 1-n in accordance with adata aggregation approach. The approach includes at least one ofde-aggregating the encrypted data 534 into a decode threshold number(e.g., n) of encrypted data sub-segments and de-aggregating theencrypted data 534 such that at least one encrypted data sub-segmentincludes an encrypted representation of a data record associated with adistributed computing partial task. The de-aggregator 606 is furtheroperable to generate n descriptors 1-n for corresponding encrypted datasub-segments of the encrypted data sub-segments 1-n. Each descriptor ofdescriptors 1-n may include at least one of a source name, a datasegment identifier (ID), and a slice name. For example, thede-aggregator 606 generates descriptors 1-n as slice names correspondingto encrypted data sub-segments 1-n, where each slice name includes acommon source name, a common data segment ID, and unique pillar IDs whenthe encrypted data 534 includes an encrypted data segment.

Each sub-key generator 516 of the n sub-key generators 516 generates asub-key of the n sub-keys based on the master key 532 and an associateddescriptor of descriptors 1-n. For example, a second sub-key generator516 utilizes the master key 532 and a descriptor 2 to generate a sub-key2. The generating includes utilizing a deterministic functions includingat least one of the hashing function (e.g., message digest algorithm 5(MD5)), the mask generating function (MGF), the hash-based messageauthentication code (HMAC), and the sponge function. The generating mayfurther include truncating an interim result of the deterministicfunction to provide a desired key length of the sub-keys 1-n.

Each decryptor 608 of the n decryptors 608 decrypts an associatedencrypted data sub-segment of the n encrypted data sub-segments 1-nutilizing a corresponding sub-key of the n sub-keys 1-n to reproduce anassociated data sub-segment of the n data sub-segments 1-n. For example,a first decryptor 608 decrypts encrypted data sub-segment 1 utilizing asub-key 1 to produce a data sub-segment 1. The de-partition function 610aggregates the n data sub-segments 1-n to reproduce the data segment152. For example, the de-partition function 610 sequentially aggregatesdata sub-segment 1 through data sub-segment n to reproduce the datasegment 152.

Each sub-key generator 516 of the n sub-key generators 516 outputs anassociated sub-key of the n sub-keys 1-n to a corresponding DSTexecution unit of the n DST execution units to enable the correspondingDST execution unit to decrypt and further process the correspondinglocally stored slice that includes an encrypted sub-segment. Forexample, the first sub-key generator 516 outputs the sub-key 1 to DSTexecution unit 1. For each DST execution unit of the n DST executionunits 1-n, the DST execution unit obtains the slice and decrypts theslice utilizing an associated sub-key to reproduce a corresponding datasub-segment of the data sub-segments 1-n. The obtaining includes atleast one of retrieving the slice from the local memory of the DSTexecution unit and receiving the slice from a DST client module. Theobtaining may further include de-combining the slice to produce acorresponding encrypted data sub-segment and a portion of the masked key538. For example, DST execution unit 1 receives a slice 1 and a sub-key1, de-combines slice 1 to reproduce encrypted data sub-segment 1 and acorresponding portion of the masked key 532, and decrypts the encrypteddata sub-segment 1 utilizing sub-key 1 to reproduce data sub-segment 1.The DT execution module 90 executes a partial task on the datasub-segment to produce a partial result of partial results 1-n. Theexecuting further includes receiving the partial task. For example, theDT execution module 90 of DST execution unit 1 receives a partial task 1and performs the partial task 1 on the data sub-segment 1 to producepartial results 1.

FIG. 45C is a flowchart illustrating an example of decoding slices. Themethod begins at step 616 where a processing module (e.g., of adistributed storage and task (DST) client module) receives at least adecode threshold number of encoded data slices of a set of encoded dataslices. The set of encoded data slices includes a decode thresholdnumber of encrypted data sub-segments and additional error coded slices(e.g., a pillar width number minus the decode threshold number). Thereceiving may include one or more of generating read slice requests,sending the read slice requests to a decode threshold number of DSTexecution units, and receiving the decode threshold number of encodeddata slices from the decode threshold number of DST execution units.

The method continues at step 618 where the processing module decodes theat least the decode threshold number of encoded data slices utilizing adispersed storage error coding function to reproduce a secure datasegment. The method continues at step 620 where the processing modulede-combines (e.g., de-append to, de-interleave) the secure data segmentto reproduce encrypted data and a masked key. The method continues withat step 622 where the processing module performs a deterministicfunction on the encrypted data to produce transformed data. The methodcontinues at step 624 where the processing module de-masks the maskedkey utilizing the transformed data to reproduce a master key. Forexample, the processing module performs an exclusive OR function on themasked key and the transformed data to reproduce the master key.

The method continues at step 626 where the processing modulede-aggregates the encrypted data to reproduce a decode threshold numberof encrypted data sub-segments. For example, the processing modulede-aggregates the encrypted data to reproduce three encrypted datasub-segments when the decode threshold number is three. For eachencrypted data sub-segment, the method continues at step 628 where theprocessing module generates a sub-key based on the master key and adescriptor associated with the encrypted data partition. The generatingincludes receiving the descriptor associated with the encrypted datasub-segment and performing a deterministic function on the master keyutilizing the descriptor to reproduce the sub-key. For example, theprocessing module receives the descriptor and performs a hash basedmessage authentication code (HMAC) function on the master key utilizingthe descriptor to reproduce the sub-key.

The method continues at step 630 where the processing module outputs thedecode threshold number of sub-keys to a corresponding decode thresholdnumber of DST execution units where each DST execution unit obtains acorresponding encrypted data sub-segment (e.g., retrieves a locallystored slice) and decrypts the encrypted data sub-segment utilizing areceived sub-key to reproduce a corresponding data sub-segment forfurther processing (e.g., execution of a partial task on the datapartition to produce a partial result). For each encrypted datasub-segment, the method continues at step 632 where the processingmodule decrypts the encrypted data sub-segment utilizing a correspondingsub-key to reproduce a corresponding data sub-segment when data isdesired. The method continues at step 634 where the processing modulede-partitions (e.g., aggregates) the decode threshold number of datasub-segments to reproduce a data segment when the data is desired.

FIG. 46A is a schematic block diagram of another embodiment of adistributed storage and task (DST) processing unit 16 and a set of DSTexecution units 1-x. The set of DST execution units 1-4 may include anynumber of DST execution units and is divided into a data slice sub-setof units and a redundancy sub-set of units. For example, the data slicesub-set of units includes a number of units corresponding to a decodethreshold number of a dispersed storage error encoding function and theredundancy sub-set of units includes a number of units corresponding toa redundancy number of the dispersed storage error encoding function.Each of the DST execution units includes a memory 640 and a distributedtask (DT) execution module 90.

The system functions to distribute data to the decode threshold numberof DST execution units 1-3n (e.g. the data slice sub-set of units) forexecution of a decode threshold number of partial tasks 1-3 to produce adecode threshold number of partial results 1-3. The partial results mayinclude preliminary partial results 642, where each DT execution module90 performs a common task of the partial tasks on the data to producethe preliminary partial results. Each DT execution module 90 generatesinterim data A-B based on the preliminary partial results 642 and storesthe interim data A-B in the memory 640 of each of the decode thresholdnumber of DST execution units for subsequent unique partial sub-taskprocessing.

The DST processing unit 16 generates and outputs a decode thresholdnumber of data slice groups 1-3 and corresponding decode thresholdnumber of partial tasks 1-3 to the decode threshold number of DSTexecution units 1-3. Each slice group of the slice groups 1-3 includesone or more slices. The DST processing unit 16 issues an associatederror coded data slice 4 to DST execution unit 4 associated with storageof error coded slices to provide reliable recovery of the data slicegroups. Each DST execution unit of the decode threshold number of DSTexecution units 1-3 receives and stores the corresponding data slicegroup and corresponding partial tasks in the memory 640 of the DSTexecution unit. Each DT execution module 90 of the decode thresholdnumber of DST execution units 1-3 performs the common task of acorresponding partial task on at least a portion of the data slice groupto produce a corresponding preliminary partial result. For example, DTexecution module 90 of DST execution unit 1 performs the common task ofpartial task 1 on a data slice 1 of data slice group 1 to produce afirst preliminary partial result of the preliminary partial results 642,DT execution module 90 of DST execution unit 2 performs the common taskof partial task 2 on a data slice 1 of data slice group 2 to produce asecond preliminary partial result, and DT execution module 90 of DSTexecution unit 3 performs the common task of partial task 3 on a dataslice 1 of data slice group 3 to produce a third preliminary partialresult.

Each DT execution module 90 of DST execution units 1-3 generates acorresponding interim data of the interim data for storage in the memory640 associated with the DT execution module 90. The decode thresholdnumber of interim data A, interim data B, and interim data C forms aninterim data segment for at least temporary storage in the set of DSTexecution units 1-4. Each DT execution module 90 of DST execution units1-3 executes a unique partial sub-task on a corresponding interim datato produce a partial result. For example, DT execution module 90 of DSTexecution unit 1 performs a first unique partial sub-task on interimdata A to produce partial results 1, DT execution module 90 of DSTexecution unit 2 performs a second unique partial sub-task on interimdata B to produce partial results 2, and DT execution module 90 of DSTexecution unit 3 performs a third unique partial sub-task on interimdata C to produce partial results 3.

The DT execution modules 90 of the decode threshold number of DSTexecution units 1-3 generates partial redundancy data 1-3 based on theinterim data A-C. For example, the DT execution module 90 of DSTexecution unit 1 generates a partial error coded slice for interim dataA with regards to a redundancy data slice 4, the DT execution module 90of DST execution unit 2 generates a partial error coded slice forinterim data B with regards to the redundancy data slice 4, and the DTexecution module 90 of DST execution unit 3 generates a partial errorcoded slice for interim data C with regards to the redundancy data slice4 when a decode threshold number is three and a pillar width is four fordispersed storage of the interim data segment.

A DT execution module 90 of each DST execution unit associated withstorage of error coded slices of the interim data segment receives adecode threshold number of partial error coded slices and decodes thedecode threshold number of partial error coded slices to produce anassociated error coded interim result slice for storage in a slicememory of the DST execution unit as a redundancy data slice. Forexample, the DT execution module 90 of DST execution unit 4 receives thedecode threshold number of partial error coded slices from the decodethreshold number of DST execution units 1-3 and performs an exclusive ORfunction on the decode threshold number of partial error coded slices toproduce the error coded interim result slice 4 for storage in the memory640 of DST execution unit 4. Any interim data A-C may be rebuilt byretrieving a decode threshold number of interim data and redundancydata, decoding the decode threshold number of interim data in redundancydata to reproduce the interim data segment, and encoding the interimdata segment to reproduce the interim data to be rebuilt.

FIG. 46B is a schematic block diagram of another embodiment of adistributed computing system that includes a distributed storage andtask (DST) execution unit set 650. The DST execution unit set 650includes a set of DST execution units 1-4. Alternatively, the DSTexecution unit set 650 may include any number of DST execution units.Each DST execution unit of the set of DST execution units 1-4 isassociated with at least one processing module and a memory. Forexample, the at least one processing module includes software stored ina DST execution unit. As another example, the at least one processingmodule includes firmware stored in the DST execution unit. As yetanother example, the at least one processing module includes acoprocessor implemented within the DST execution unit. The memory may beimplemented utilizing one or more of a memory array, a memory device, aplurality of memory devices, an optical disk drive memory device, amagnetic disk drive memory device, and a solid state memory device. Forexample, DST execution unit 1 includes a first module 652 and memory660, DST execution unit 2 includes a second module 654 and memory 662,DST execution unit 3 includes a third module 656 and memory 664, and DSTexecution unit 4 includes a redundancy module 658 and memory 666.

A first decode threshold number of DST execution units of the set of DSTexecution units may be utilized to process a partial task set 670 ondata 668 to produce partial results. Remaining DST execution units ofthe set of DST execution units (e.g., a pillar width number minus thedecode threshold number) may be utilized to store the redundancy data672 to provide an ability to recover information stored by the decodethreshold number of DST execution units when one or more of the decodethreshold number of DST execution units is not available. For example,three DST execution units 1-3 include first second third modules 652,654, and 656 and a fourth DST execution unit 4 includes the redundancymodule 658 when the pillar width is 4 and the decode threshold is 3.

The system functions to perform the partial task set 670 on the data 668to produce partial results. The performing of the partial task set 670on the data 668 includes primary functions where a first primaryfunction includes receiving the set of partial tasks 670 and the data668, a second primary function includes executing at least some of thepartial task set 670 on at least some of the data 668 to produce apreliminary partial results set 642, a third primary function includesgenerating interim data based on at least some of the set of preliminarypartial results 642, a fourth primary function includes generating theredundancy data 672, and a fifth primary function includes executingfurther partial tasks to produce the partial results.

The first primary function to receive the set of partial tasks 670 andthe data 668 includes a series of receiving steps performed by the setof modules (e.g., 652, 654, 656). A partial task of the set of partialtasks 670 includes a common task and a unique partial sub-task. Thecommon task corresponds to a function to identify a commoncharacteristic of portions of the data 668. The unique partial sub-taskcorresponds to a function to uniquely categorize the commoncharacteristic of the portions of the data based on a unique parameter.For example, a common task includes searching the data 668 to identifyhamburger prices across all regions of the United States, a first uniquepartial sub-task includes identifying, within the identified hamburgerprices, hamburger prices for fast food restaurants, a second uniquepartial sub-task includes identifying, within the identified hamburgerprices, hamburger prices for non-fast food restaurants, and a thirdunique partial sub-task includes identifying, within the identifiedhamburger prices, hamburger prices for retail food stores.

A first receiving step of the series of receiving steps includes thefirst module 652 receiving, via an interface associated with the firstDST execution unit, a first partial task (e.g., partial task 1) of theset of partial tasks 670 and a first portion of the data (e.g., dataportion 1), where the first partial task includes the common task andthe first unique partial sub-task. A second receiving step includes thesecond module 654 receiving, via an interface associated with the secondDST execution unit, a second partial task (e.g., partial task 2) of theset of partial tasks 670 and a second portion of the data (e.g., dataportion 2), where the second partial task includes the common task andthe second unique partial sub-task. A third receiving step includes thethird module 656 receiving, via an interface associated with the thirdDST execution unit, a third partial task (e.g., partial task 3) of theset of partial tasks 670 and a third portion of the data (e.g., dataportion 3), where the third partial task includes the common task andthe third unique partial sub-task.

A fourth receiving step includes the set of modules 652-656 allocatingthe data 668 into the first, second, and third portions of the data 668based on at least one of a time parameter, a geographic parameter, and asource parameter. For example, the first module 652 allocates a firsthour of a data stream to the first portion of the data, the secondmodule 654 allocates a second hour of the data stream to the secondportion of the data, and the third module 656 allocates a third hour ofthe data stream to the third portion of the data when basing theallocation on the time parameter. As another example, the first module652 allocates an East Coast portion of a national database to the firstportion of the data, the second module 654 allocates a Midwest portionof the national database to the second portion of the data, and thethird module 656 allocates a West Coast portion of the national databaseto the third portion of the data when basing the allocation on thegeographic parameter. As yet another example, the first module 652allocates information from an Internet WebCrawler to the first portionof the data, the second module 654 allocates information from a mediaserver to the second portion of the data, and the third module 656allocates information from a private database to the third portion ofthe data when basing the allocation on the source parameter.

The second primary function to execute the at least some of the partialtask set 670 on the at least some of the data 668 to produce thepreliminary partial results set 642 includes executing, by the set ofmodules (e.g., 652-656), the common task on the data 668 to produce theset of preliminary partial results 642. The first module 652 executesthe common task on the first portion of the data (e.g., data portion 1)to produce a first preliminary partial result of the set of preliminarypartial results 642. The second module 654 executes the common task onthe second portion of the data (e.g., data portion 2) to produce asecond preliminary partial result of the set of preliminary partialresults 642. The third module 656 executes the common task on the thirdportion of the data (e.g., data portion 3) to produce a thirdpreliminary partial result of the set of preliminary partial results642.

The third primary function to generate the interim data based on the atleast some of the set of preliminary partial results 642 includes aseries of interim data steps. In a first interim data step each of thefirst, second, and third modules 652-656 generates the interim databased on at least some of the set of preliminary partial results 642.The first module 652 generates first interim data (e.g., interim data 1)based on the at least some of the set of preliminary partial results642. The first module 652 generates the first interim data by processingat least one of the first, second, and third preliminary partial resultsto produce the first interim data. The processing includes selecting theat least one of the first, second, and the third preliminary partialresults based on one or more of a predetermination, another uniquepartial sub-task, and a local preliminary partial result. For example,the first module 652 selects third preliminary partial results when thethird pulmonary partial results are required for execution of the thirdunique partial sub-task. The second module 654 generates second interimdata (e.g., interim data 2) based on the at least some of the set ofpreliminary partial results 642. The third module 656 generates thirdinterim data (e.g., interim data 3) based on the at least some of theset of preliminary partial results 642.

In a second interim data step of the series of interim data steps, eachof the first, second, and third modules 652-656 facilitate storage ofthe interim data in the memories 660-664 that are associated with thefirst DST execution unit, the second DST execution unit, and the thirdDST execution unit. The first module 652 facilitates storage of thefirst interim data in memory 660 associated with the first DST executionunit. The second module 654 facilitates storage of the second interimdata in memory 662 associated with the second DST execution unit. Thethird module 656 facilitates storage of the third interim data in memory664 associated with the third DST execution unit.

The fourth primary function to generate the redundancy data 672 includesa series of redundancy steps. In a first redundancy step, the firstmodule 652 generates first partial redundancy data (e.g., partialredundancy data 1) based on the first interim data and sends the firstpartial redundancy data to each DST execution unit associated withstoring the redundancy data 672. For example, the first module 652 sendsthe first partial redundancy data to the redundancy module 658 of DSTexecution unit 4 when one DST execution unit is utilized for storage ofthe redundancy data 672. The generating of the first partial redundancydata includes at least one of utilizing the first interim data (e.g., afirst slice of a set of slices) as the first partial redundancy data andgenerating a fourth partially encoded slice (e.g., to construct a pillar4 slice of the set of slices) based on the first interim data (e.g., thefirst slice of the set of slices). The generating of the fourthpartially encoded slice based on the first interim data includesobtaining an encoding matrix, reducing the encoding matrix to produce asquare matrix to include rows associated with the decode thresholdnumber of slices of the set of slices (e.g., rows 1-3), inverting thereduced matrix to produce a reduced inverted matrix, matrix multiplyingthe reduced inverted matrix by the first interim data as a vector toproduce a data vector, and matrix multiplying the data vector by a rowof the encoding matrix corresponding to the pillar 4 slice to producethe fourth partially encoded slice.

In a second redundancy step, the second module 654 generates secondpartial redundancy data (e.g., partial redundancy data 2) based on thesecond interim data and sends the second partial redundancy data to thefourth DST execution unit. In a third redundancy step, the third module656 generates third partial redundancy data based on the third interimdata and sends the third partial redundancy data to the fourth DSTexecution unit. In a fourth redundancy step, the redundancy module 658generates the redundancy data 672 for the first, second, and thirdinterim data based on the first, second, and third partial redundancydata. The generating includes at least one of adding a decode thresholdnumber of the first, second, and third partial redundancy data in afield associated with a dispersed storage error coding function, e.g.,exclusive OR, and decoding the decode threshold number of the first,second, and third partial redundancy data using a dispersed storageerror coding function to produce the redundancy data 672.

The fifth primary function to execute the further partial tasks toproduce the partial results includes at least one of the first, second,and third modules 652-656 executing a corresponding one or more uniquepartial sub-tasks on at least one of a corresponding portion of the data668 and a corresponding portion of the interim data to produce thepartial results. The first module 652 executes the first unique partialsub-task on at least one of the first portion of the data and the firstinterim data to produce a first partial result. The second module 654executes the second unique partial sub-task on at least one of thesecond portion of the data and the second interim data to produce asecond partial result. The third module 656 executes the third uniquepartial sub-task on at least one of the third portion of the data andthe third interim data to produce a third partial result. Each of thefirst, second, and third modules 652-656 outputs the partial results.The first module 652 outputs, via the interface associated with thefirst DST execution unit, the first partial result. The second module654 outputs, via the interface associated with the second DST executionunit, the second partial result. The third module 656 outputs, via theinterface associated with the third DST execution unit, the thirdpartial result.

FIG. 46C is a flowchart illustrating an example of storing an interimresult. The method begins at step 680 where a set of distributed storageand task (DST execution units receive a set of partial tasks and data,where a partial task of the set of partial tasks includes a common taskand a unique partial sub-task. The common task corresponds to a functionto identify a common characteristic of portions of the data and theunique partial sub-task corresponding to a function to uniquelycategorize the common characteristic of the portions of the data basedon a unique parameter. The receiving includes a series of receivingsteps. A first receiving step includes a first DST execution unit of theset of DST execution units receiving a first partial task of the set ofpartial tasks and a first portion of the data, where the first partialtask includes the common task and a first unique partial sub-task. Asecond receiving step includes a second DST execution unit of the set ofDST execution units receiving a second partial task of the set ofpartial tasks and a second portion of the data, where the second partialtask includes the common task and a second unique partial sub-task. Athird receiving step includes a third DST execution unit of the set ofDST execution units receiving a third partial task of the set of partialtasks and a third portion of the data when a third DST execution unit isto be included in the receiving, where the third partial task includesthe common task and a third unique partial sub-task.

A fourth receiving step of the series of receiving steps includes one ormore of a variety of data receiving approaches. A first data receivingapproach includes the set of DST execution units allocating the datainto the first, second, and third portions of the data based on a timeparameter. A second data receiving approach includes the set of DSTexecution units allocating the data into the first, second, and thirdportions of the data based on a geographic parameter. A third datareceiving approach includes the set of DST execution units allocatingthe data into the first, second, and third portions of the data based ona source parameter.

The method continues at step 682 where the set of DST execution unitsexecutes the common task on the data to produce a set of preliminarypartial results. The executing includes a series of common taskexecuting steps. In a first common task executing step, the first DSTexecution unit executes the common task on the first portion of the datato produce a first preliminary partial result of the set of preliminarypartial results. In a second common task executing step, the second DSTexecution unit executes the common task on the second portion of thedata to produce a second preliminary partial result of the set ofpreliminary partial results. In a third common task executing step, thethird DST execution unit executes the common task on the third portionof the data to produce a third preliminary partial result of the set ofpreliminary partial results.

The method continues at step 684 where the first DST execution unitgenerates first interim data based on the at least some of the set ofpreliminary partial results. The generating includes processing at leastone of the first, second, and third preliminary partial results toproduce the first interim data. The processing includes selecting the atleast one of the first, second, and the third preliminary partialresults based on one or more of a predetermination, another uniquepartial sub-task, and a local preliminary partial result. The methodcontinues at step 686 where the second DST execution unit generatessecond interim data based on the at least some of the set of preliminarypartial results. The method continues at step 688 where the third DSTexecution unit generates third interim data based on the at least someof the set of preliminary partial results.

The method continues at step 690 where the first DST execution unitexecutes the first unique partial sub-task on at least one of: the firstportion of the data and the first interim data to produce a firstpartial result. Alternatively, or in addition to, the second DSTexecution unit executes the second unique partial sub-task on at leastone of: the second portion of the data and the second interim data toproduce the second partial result. Alternatively, or in addition to, thethird DST execution unit executes the third unique partial sub-task onat least one of: the third portion of the data and the third interimdata to produce the third partial result.

The method continues at step 692 where the first DST execution unitgenerates first partial redundancy data based on the first interim data.The method continues at step 694 where the second DST execution unitgenerates second partial redundancy data based on the second interimdata. The method continues at step 696 where the third DST executionunit generates third partial redundancy data based on the third interimdata. The method continues at step 698 where a fourth DST execution unitof the set of DST execution units generates redundancy data for thefirst, second, and third interim data based on the first, second, andthird partial redundancy data.

FIG. 47A is a schematic block diagram of another embodiment of adistributed computing system that includes a user device 14, adistributed storage and task (DST) processing unit 16, a distributedstorage and task network (DSTN) managing unit 18, and a DST executionunit 36. The DST execution unit 36 includes a slice memory 700, acomputing task memory 702, and a distributed task (DT) execution module90. The system functions to generate data slices 704 for partial taskexecution to produce partial results 708.

The DSTN managing unit 18 maintains a registry that includes a pluralityof registry entries. At least one of the plurality of registry entriesincludes a user device identifier of the user device 14 andcorresponding permissions associated with the user device 14. Thepermissions include one or more of an allowed partial task type, anumber of allowed partial test types, a number of allowed simultaneouspartial task execution requests, a maximum partial task executionresource utilization level per unit of time, and a cumulative partialtask execution resource utilization level. The maintaining includesgenerating a registry entry for the user device 14, modifying theregistry entry based on task execution information 712, and outputtingpermissions information 710 to one or more elements of the system. Thepermissions information 710 includes one or more registry entries of theplurality of registry entries. The task execution information 712includes information with regards to the execution of tasks by the DTexecution module 90 (e.g., partial tasks executed, partial taskexecution resource utilization information). For example, the DSTNmanaging unit 18 updates the registry entry associated with the userdevice 14 to include an updated view of partial task execution resourceutilization level based on partial task execution resource utilizationlevel information received in the task execution information 712.

One or more elements the system (e.g., the DS processing unit 16, the DTexecution module) utilize the permissions information 710 with regardsto authorizing a request 38 to facilitate the execution of partial tasks706. The DS processing unit 16 receives data 40 and/or a task request 38and utilizes the permissions information 710 to authorize the request38. The authorizing includes one or more of indicating that the request38 is authorized when request 38 and a user identifier associated withuser device 14 compares favorably to the permissions information 700 andwith regards to an allowed partial test type, indicating that therequest 38 is authorized when a number of current simultaneous partialtask execution requests has not exceeded a number of allowedsimultaneous partial task execution requests, and indicating that therequest 38 is authorized when a cumulative partial task executionresource utilization level associated with the user device 14 comparesfavorably (e.g., less than) to a maximum partial task execution resourceutilization level for the user device 14.

When the request 38 is authorized, the DST processing unit 16 encodesdata 40 to produce data slices 704 and produces the partial tasks 706associated with the task request 38. A partial task 706 of the partialtasks 706 includes one or more of a task identifier, a task descriptor,a task, a requesting entity identifier, and the permissions information.The DST processing unit 16 sends the data slices 704 and partial tasks706 to the DST execution unit 36. The DST execution unit 36 stores thedata slices 704 in the slice memory 700 and stores the partial tasks 706in the computing task memory 702.

The DT execution module 90 retrieves data slices 704 from the slicememory 700 and retrieves partial tasks 706 from the computing taskmemory 702. The DT execution module 90 may authorize the partial tasks706 with regards to the permissions information 710. The authorizingincludes directly authorizing and receiving an authorization indicationfrom the DST processing unit 16. When authorized, the DT executionmodule 90 executes one or more of the partial tasks 706 on one or moreof the data slices 704 to produce partial results 708. The DT executionmodule 90 generates the task execution information 712 based onexecution of the partial tasks 706 to produce the partial results 708.The DT execution module 90 outputs the task execution information 712 tothe DSTN managing unit 18. The DT execution module 90 outputs thepartial results 708 to the user device 14. The outputting includessending the partial results 708 directly to the user device 14 andsending the partial results 708 to the user device 14 via the DSTprocessing unit 16.

FIG. 47B is a flowchart illustrating an example of authorizing a partialtask execution request. The method begins at step 714 where a processingmodule (e.g., of a distributed storage and task (DST) client module, ofa distributed task (DT) execution module) receives a partial taskexecution request (e.g., from at least one of a user device, a DSTprocessing unit). The method continues at step 716 where the processingmodule identifies a requesting entity associated with the partial taskexecution request. The identifying may be based on one or more ofextraction from the request, receiving, and initiating a query. Themethod continues at step 718 where the processing module identifies apartial task associated with the partial task execution request. Theidentifying includes at least one of extracting the partial task fromthe partial task execution requests, a lookup based on a task code, andinitiating a query.

The method continues at step 720 where the processing module obtainspermissions associated with the requesting entity. The obtainingincludes at least one of accessing receiving permissions informationfrom a registry, accessing the permissions information based on anidentifier of the requesting entity to extract a registry entry,initiating a query, extracting the permissions from the request, and alookup.

The method continues at step 722 where the processing module determineswhether the partial task compares favorably with the permissions. Forexample, the processing module determines that the comparison isfavorable when the permissions indicate that the requesting entity isauthorized for a task type of the partial task. As another example, theprocessing module determines that the comparison is favorable when thepermissions indicates that a cumulative partial task executionutilization level is less than a utilization level threshold. The methodbranches to step 726 when the comparison is favorable. The methodcontinues to step 724 when the comparison is unfavorable. The methodcontinues at step 724 where the processing module denies the partialtask execution request. The denying includes one or more of generating adenial response that includes an indication that the partial taskexecution request is denied and sending the denial response to at leastone of the requesting entity and a distributed storage and task network(DSTN) managing unit.

The method continues at step 726 where the processing module executesthe partial task when the partial task compares favorably with thepermissions. For example, the processing module executes the partialtask on a corresponding data slice to produce partial results. Theexecution may further include outputting the partial results to therequesting entity. The method continues at step 728 where the processingmodule generates task execution information based on execution of thepartial task on me data slice to produce the partial results. The methodcontinues at step 730 where the processing module outputs the taskexecution information. The outputting includes sending the taskexecution information to at least one of the DSTN managing unit, therequesting entity, and the DST processing unit.

FIG. 48A is a schematic block diagram of another embodiment of adistributed computing system that includes a user device 14, adistributed storage and task (DST) processing unit 16, and at least twoDST execution units 36. Each DST execution unit 36 and the at least twoDST execution units 36 includes a slice memory 700, a computing taskmemory 702, and a distributed task (DT) execution module 90. The systemfunctions to generate data slices for partial task execution to producepartial results 708.

The DS processing unit 16 receives data 40 and/or a task request 38 andencodes data 40 to produce at least two groups of data slices 1-2 andproduces at least two groups of partial tasks 1-2 associated with thetask request 38. The data 40 may include a plurality of data records.The DST processing unit 16 may encode a data record of the plurality ofdata records to produce a last slice of a first group of data slices 1and a first slice of a second group of data slices 2. A first group ofpartial tasks 1 may include a partial task associated with the datarecord. The DST processing unit 16 sends the at least two groups of dataslices 1-2 and at least two groups of partial tasks 1-2 to a first DSTexecution unit 36 of the at least two DST execution units 36. The firstDST execution unit 36 stores data slices 1 in the slice memory 700 ofthe first DST execution of 36 and stores the partial tasks 1 in thecomputing task memory 702 of the first DST execution unit 36.

The DT execution module 90 of the first DST execution and 36 retrievesdata slices 1 from the slice memory 700 and retrieves partial tasks 1from the computing task memory 702. The DT execution module 90determines whether the slice memory 700 contains every data slicerequired to execute partial tasks 1. When the DT execution module 90determines that slice memory does not contain every data slice requiredto execute partial tasks 1, the DT execution module 90 identifies atleast one other data slice. For example, the DT execution moduleidentifies a first slice of the data slices 2 when a data recordassociated with a partial task 1 includes a last slice of the dataslices 1 and the first slice of the data slices 2. The DT executionmodule 90 generates a slice request 734 to obtain the at least one otherdata slice from another DST execution unit 36. The slice request 734includes one or more of a slice name associated with the at least oneother data slice, a requesting entity identifier, a copy of the partialtask 1, and an access credential (e.g., a signature, a signed copy ofthe partial task 1). The DT execution module sends the slice request 734to the other DST execution unit 36.

The DT execution module 90 of the other DST execution unit 36 receivesthe slice request 734 and may authorize the slice request 734 based onthe request. For example, the DT execution module 90 of the other DSTexecution of 36 verifies a signature of the slice request 734. When therequest is authorized, the DT execution module 90 of the other DSTexecution of 36 facilitates sending the at least one other data slice tothe DST execution unit 36. The DST execution 36 stores the at least oneother data slice (e.g., data slice 2) in the slice memory 700. The DTexecution module 90 may determine whether the slice memory 700 containsevery data slice required to execute partial tasks 1. When the DTexecution module 90 determines that slice memory 700 contains every dataslice required to execute partial tasks 1, the DT execution module 90executes one or more partial tasks of partial tasks 1 on data slicesretrieved from the slice memory (e.g., data slices 1, data slices 2) toproduce partial results 708. For example, the DT execution module 90aggregates data slice 1 and data slice 2 to reproduce the data recordand executes the one or more partial tasks on the data record to producethe partial results 708. The DT execution module outputs the partialresults 708 to the DST processing unit 16 and/or the user device 14.Alternatively, or in addition to, the DT execution module 90 of theother DST execution unit 36 may perform a partial task 2 on a data slice2 to produce partial results 708.

FIG. 48B is a flowchart illustrating an example of obtaining a datarecord. The method begins at step 740 where a processing module (e.g.,of a distributed task (DT) execution module) receives a data slice andan associated partial task. The method continues at step 742 where theprocessing module identifies a data record associated with the dataslice. The identifying may be based on one or more obtaining a slicename of the data slice, performing a data record identifier lookup in aslice name to data list, and extracting a data record identifier fromthe data slice. When the data record includes another data slice, themethod continues at step 744 where the processing module generates aslice request. The processing module may determine whether the datarecord includes the other data slice based on at least one of performingany data record ID to slice name lookup, receiving a list of slicenames, and a query. The generating of the slice request includes one ormore of identifying a slice name associated with the other data slice,identifying another distributed storage and task (DST) execution unitassociated with the other data source, generating a partial task fieldentry that includes at least a portion of the associated partial task,and generating a credential field entry that includes a signature.

The method continues at step 746 where the processing module outputs theslice request to the other DST execution unit. The method continues atstep 748 where the processing module receives the other data slice fromthe other DST execution unit. The method continues at step 750 where theprocessing module performs the partial task on the data slice and theother data slice to produce partial results. The performing may includeone or more of aggregating at least a portion of the data slice and atleast a portion of the other data slice to produce the data record andexecuting at least a portion of the associated partial task on the datarecord to produce the partial results.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method comprises: receiving, by a set ofdistributed storage and task (DST) execution units, a set of partialtasks and data, wherein a partial task of the set of partial tasksincludes a common task and a unique partial sub-task; executing, by theset of DST execution units, the common task on the data to produce a setof preliminary partial results; generating, by a first DST executionunit of the set of DST execution units, first interim data based on theat least some of the set of preliminary partial results; and executing,by the first DST execution unit, a first unique partial sub-task on atleast one of: a first portion of the data and the first interim data toproduce a first partial result.
 2. The method of claim 1 furthercomprises: receiving, by the first DST execution unit, a first partialtask of the set of partial tasks and the first portion of the data,wherein the first partial task includes the common task and the firstunique partial sub-task; receiving, by a second DST execution unit, asecond partial task of the set of partial tasks and a second portion ofthe data, wherein the second partial task includes the common task and asecond unique partial sub-task; and receiving, by a third DST executionunit, a third partial task of the set of partial tasks and a thirdportion of the data, wherein the third partial task includes the commontask and a third unique partial sub-task.
 3. The method of claim 2further comprises at least one of: allocating the data into the first,second, and third portions of the data based on a time parameter;allocating the data into the first, second, and third portions of thedata based on a geographic parameter; and allocating the data into thefirst, second, and third portions of the data based on a sourceparameter.
 4. The method of claim 2, wherein the executing the commontask on the data to produce the set of preliminary partial resultscomprises: executing, by the first DST execution unit, the common taskon the first portion of the data to produce a first preliminary partialresult of the set of preliminary partial results; executing, by thesecond DST execution unit, the common task on the second portion of thedata to produce a second preliminary partial result of the set ofpreliminary partial results; and executing, by the third DST executionunit, the common task on the third portion of the data to produce athird preliminary partial result of the set of preliminary partialresults.
 5. The method of claim 4, wherein the generating the firstinterim data comprises: processing at least one of the first, second,and third preliminary partial results to produce the first interim data.6. The method of claim 1 further comprises: the common taskcorresponding to a function to identify a common characteristic ofportions of the data; and the unique partial sub-task corresponding to afunction to uniquely categorize the common characteristic of theportions of the data based on a unique parameter.
 7. The method of claim1 further comprises: generating, by a second DST execution unit of theset of DST execution units, second interim data based on the at leastsome of the set of preliminary partial results; and generating, by athird DST execution unit of the set of DST execution units, thirdinterim data based on the at least some of the set of preliminarypartial results.
 8. The method of claim 7 further comprises: generating,by the first DST execution unit, first partial redundancy data based onthe first interim data; generating, by the second DST execution unit,second partial redundancy data based on the second interim data;generating, by the third DST execution unit, third partial redundancydata based on the third interim data; and generating, by a fourth DSTexecution unit of the set of DST execution units, redundancy data forthe first, second, and third interim data based on the first, second,and third partial redundancy data.
 9. A distributed computing systemcomprises: a set of modules associated with a set of distributed storageand task (DST) execution units, wherein the set of modules is operableto: receive a set of partial tasks and data, wherein a partial task ofthe set of partial tasks includes a common task and a unique partialsub-task; and execute the common task on the data to produce a set ofpreliminary partial results, wherein a first module of the set ofmodules is operable to: generate first interim data based on the atleast some of the set of preliminary partial results; facilitate storageof the first interim data in memory associated with a first DSTexecution unit; execute a first unique partial sub-task on at least oneof: a first portion of the data and the first interim data to produce afirst partial result; and output, via an interface associated with thefirst DST execution unit, the first partial result.
 10. The distributedcomputing system of claim 9 further comprises: the first module furtherfunctions to receive, via the interface associated with the first DSTexecution unit, a first partial task of the set of partial tasks and thefirst portion of the data, wherein the first partial task includes thecommon task and the first unique partial sub-task; a second module ofthe set of modules functions to receive, via an interface associatedwith a second DST execution unit, a second partial task of the set ofpartial tasks and a second portion of the data, wherein the secondpartial task includes the common task and a second unique partialsub-task; and a third module of the set of modules functions to receive,via an interface associated with a third DST execution unit, a thirdpartial task of the set of partial tasks and a third portion of thedata, wherein the third partial task includes the common task and athird unique partial sub-task.
 11. The distributed computing system ofclaim 10 further comprises: the set of modules is further operable to:allocate the data into the first, second, and third portions of the databased on a time parameter; allocate the data into the first, second, andthird portions of the data based on a geographic parameter; and allocatethe data into the first, second, and third portions of the data based ona source parameter.
 12. The distributed computing system of claim 10,wherein the set of modules functions to execute the common task on thedata to produce the set of preliminary partial results by: executing, bythe first module, the common task on the first portion of the data toproduce a first preliminary partial result of the set of preliminarypartial results; executing, by the second module, the common task on thesecond portion of the data to produce a second preliminary partialresult of the set of preliminary partial results; and executing, by thethird module, the common task on the third portion of the data toproduce a third preliminary partial result of the set of preliminarypartial results.
 13. The distributed computing system of claim 12,wherein the first module generates the first interim data by: processingat least one of the first, second, and third preliminary partial resultsto produce the first interim data.
 14. The distributed computing systemof claim 9 further comprises: the common task corresponding to afunction to identify a common characteristic of portions of the data;and the unique partial sub-task corresponding to a function to uniquelycategorize the common characteristic of the portions of the data basedon a unique parameter.
 15. The distributed computing system of claim 9further comprises: a second module of the set of modules functions togenerate second interim data based on the at least some of the set ofpreliminary partial results; and a third module of the set of modulesfunctions to generate third interim data based on the at least some ofthe set of preliminary partial results.
 16. The distributed computingsystem of claim 15 further comprises: the first module further functionsto generate first partial redundancy data based on the first interimdata; the second module further functions to generate second partialredundancy data based on the second interim data; the third modulefurther functions to generate third partial redundancy data based on thethird interim data; and a fourth module of the set of modules functionsto generate redundancy data for the first, second, and third interimdata based on the first, second, and third partial redundancy data.